introduction to statistics powerpoint presentation

Introduction to Statistics

(15 reviews)

David Lane, Rice University

Copyright Year: 2003

Publisher: David Lane

Language: English

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Reviewed by Terri Torres, professor, Oregon Institute of Technology on 8/17/23

This author covers all the topics that would be covered in an introductory statistics course plus some. I could imagine using it for two courses at my university, which is on the quarter system. I would rather have the problem of too many topics... read more

Comprehensiveness rating: 5 see less

This author covers all the topics that would be covered in an introductory statistics course plus some. I could imagine using it for two courses at my university, which is on the quarter system. I would rather have the problem of too many topics rather than too few.

Content Accuracy rating: 5

Yes, Lane is both thorough and accurate.

Relevance/Longevity rating: 5

What is covered is what is usually covered in an introductory statistics book. The only topic I may, given sufficient time, cover is bootstrapping.

Clarity rating: 5

The book is clear and well-written. For the trickier topics, simulations are included to help with understanding.

Consistency rating: 5

All is organized in a way that is consistent with the previous topic.

Modularity rating: 5

The text is organized in a way that easily enables navigation.

Organization/Structure/Flow rating: 5

The text is organized like most statistics texts.

Interface rating: 5

Easy navigation.

Grammatical Errors rating: 5

I didn't see any grammatical errors.

Cultural Relevance rating: 5

Nothing is included that is culturally insensitive.

The videos that accompany this text are short and easy to watch and understand. Videos should be short enough to teach, but not so long that they are tiresome. This text includes almost everything: videos, simulations, case studies---all nicely organized in one spot. In addition, Lane has promised to send an instructor's manual and slide deck.

Reviewed by Professor Sandberg, Professor, Framingham State University on 6/29/21

This text covers all the usual topics in an Introduction to Statistics for college students. In addition, it has some additional topics that are useful. read more

This text covers all the usual topics in an Introduction to Statistics for college students. In addition, it has some additional topics that are useful.

I did not find any errors.

Some of the examples are dated. And the frequent use of male/female examples need updating in terms of current gender splits.

I found it was easy to read and understand and I expect that students would also find the writing clear and the explanations accessible.

Even with different authors of chapter, the writing is consistent.

The text is well organized into sections making it easy to assign individual topics and sections.

The topics are presented in the usual order. Regression comes later in the text but there is a difference of opinions about whether to present it early with descriptive statistics for bivariate data or later with inferential statistics.

I had no problem navigating the text online.

The writing is grammatical correct.

I saw no issues that would be offensive.

I did like this text. It seems like it would be a good choice for most introductory statistics courses. I liked that the Monty Hall problem was included in the probability section. The author offers to provide an instructor's manual, PowerPoint slides and additional questions. These additional resources are very helpful and not always available with online OER texts.

Reviewed by Emilio Vazquez, Associate Professor, Trine University on 4/23/21

This appears to be an excellent textbook for an Introductory Course in Statistics. It covers subjects in enough depth to fulfill the needs of a beginner in Statistics work yet is not so complex as to be overwhelming. read more

This appears to be an excellent textbook for an Introductory Course in Statistics. It covers subjects in enough depth to fulfill the needs of a beginner in Statistics work yet is not so complex as to be overwhelming.

I found no errors in their discussions. Did not work out all of the questions and answers but my sampling did not reveal any errors.

Some of the examples may need updating depending on the times but the examples are still relevant at this time.

This is a Statistics text so a little dry. I found that the derivation of some of the formulas was not explained. However the background is there to allow the instructor to derive these in class if desired.

The text is consistent throughout using the same verbiage in various sections.

The text dose lend itself to reasonable reading assignments. For example the chapter (Chapter 3) on Summarizing Distributions covers Central Tendency and its associated components in an easy 20 pages with Measures of Variability making up most of the rest of the chapter and covering approximately another 20 pages. Exercises are available at the end of each chapter making it easy for the instructor to assign reading and exercises to be discussed in class.

The textbook flows easily from Descriptive to Inferential Statistics with chapters on Sampling and Estimation preceding chapters on hypothesis testing

I had no problems with navigation

All textbooks have a few errors but certainly nothing glaring or making text difficult

I saw no issues and I am part of a cultural minority in the US

Overall I found this to be a excellent in-depth overview of Statistical Theory, Concepts and Analysis. The length of the textbook appears to be more than adequate for a one-semester course in Introduction to Statistics. As I no longer teach a full statistics course but simply a few lectures as part of our Research Curriculum, I am recommending this book to my students as a good reference. Especially as it is available on-line and in Open Access.

Reviewed by Audrey Hickert, Assistant Professor, Southern Illinois University Carbondale on 3/29/21

All of the major topics of an introductory level statistics course for social science are covered. Background areas include levels of measurement and research design basics. Descriptive statistics include all major measures of central tendency and... read more

All of the major topics of an introductory level statistics course for social science are covered. Background areas include levels of measurement and research design basics. Descriptive statistics include all major measures of central tendency and dispersion/variation. Building blocks for inferential statistics include sampling distributions, the standard normal curve (z scores), and hypothesis testing sections. Inferential statistics include how to calculate confidence intervals, as well as conduct tests of one-sample tests of the population mean (Z- and t-tests), two-sample tests of the difference in population means (Z- and t-tests), chi square test of independence, correlation, and regression. Doesn’t include full probability distribution tables (e.g., t or Z), but those can be easily found online in many places.

I did not find any errors or issues of inaccuracy. When a particular method or practice is debated in the field, the authors acknowledge it (and provide citations in some circumstances).

Relevance/Longevity rating: 4

Basic statistics are standard, so the core information will remain relevant in perpetuity. Some of the examples are dated (e.g., salaries from 1999), but not problematic.

Clarity rating: 4

All of the key terms, formulas, and logic for statistical tests are clearly explained. The book sometimes uses different notation than other entry-level books. For example, the variance formula uses "M" for mean, rather than x-bar.

The explanations are consistent and build from and relate to corresponding sections that are listed in each unit.

Modularity is a strength of this text in both the PDF and interactive online format. Students can easily navigate to the necessary sections and each starts with a “Prerequisites” list of other sections in the book for those who need the additional background material. Instructors could easily compile concise sub-sections of the book for readings.

The presentation of topics differs somewhat from the standard introductory social science statistics textbooks I have used before. However, the modularity allows the instructor and student to work through the discrete sections in the desired order.

Interface rating: 4

For the most part the display of all images/charts is good and navigation is straightforward. One concern is that the organization of the Table of Contents does not exactly match the organizational outline at the start of each chapter in the PDF version. For example, sometimes there are more detailed sub-headings at the start of chapter and occasionally slightly different section headings/titles. There are also inconsistencies in section listings at start of chapters vs. start of sub-sections.

The text is easy to read and free from any obvious grammatical errors.

Although some of the examples are outdated, I did not review any that were offensive. One example of an outdated reference is using descriptive data on “Men per 100 Women” in U.S. cities as “useful if we are looking for an opposite-sex partner”.

This is a good introduction level statistics text book if you have a course with students who may be intimated by longer texts with more detailed information. Just the core basics are provided here and it is easy to select the sections you need. It is a good text if you plan to supplement with an array of your own materials (lectures, practice, etc.) that are specifically tailored to your discipline (e.g., criminal justice and criminology). Be advised that some formulas use different notation than other standard texts, so you will need to point that out to students if they differ from your lectures or assessment materials.

Reviewed by Shahar Boneh, Professor, Metropolitan State University of Denver on 3/26/21, updated 4/22/21

The textbook is indeed quite comprehensive. It can accommodate any style of introductory statistics course. read more

The textbook is indeed quite comprehensive. It can accommodate any style of introductory statistics course.

The text seems to be statistically accurate.

It is a little too extensive, which requires instructors to cover it selectively, and has a potential to confuse the students.

It is written clearly.

Consistency rating: 4

The terminology is fairly consistent. There is room for some improvement.

By the nature of the subject, the topics have to be presented in a sequential and coherent order. However, the book breaks things down quite effectively.

Organization/Structure/Flow rating: 3

Some of the topics are interleaved and not presented in the order I would like to cover them.

Good interface.

The grammar is ok.

The book seems to be culturally neutral, and not offensive in any way.

I really liked the simulations that go with the book. Parts of the book are a little too advanced for students who are learning statistics for the first time.

Reviewed by Julie Gray, Adjunct Assistant Professor, University of Texas at Arlington on 2/26/21

The textbook is for beginner-level students. The concept development is appropriate--there is always room to grow to high higher level, but for an introduction, the basics are what is needed. This is a well-thought-through OER textbook project by... read more

The textbook is for beginner-level students. The concept development is appropriate--there is always room to grow to high higher level, but for an introduction, the basics are what is needed. This is a well-thought-through OER textbook project by Dr. Lane and colleagues. It is obvious that several iterations have only made it better.

I found all the material accurate.

Essentially, statistical concepts at the introductory level are accepted as universal. This suggests that the relevance of this textbook will continue for a long time.

The book is well written for introducing beginners to statistical concepts. The figures, tables, and animated examples reinforce the clarity of the written text.

Yes, the information is consistent; when it is introduced in early chapters it ties in well in later chapters that build on and add more understanding for the topic.

Modularity rating: 4

The book is well-written with attention to modularity where possible. Due to the nature of statistics, that is not always possible. The content is presented in the order that I usually teach these concepts.

The organization of the book is good, I particularly like the sample lecture slide presentations and the problem set with solutions for use in quizzes and exams. These are available by writing to the author. It is wonderful to have access to these helpful resources for instructors to use in preparation.

I did not find any interface issues.

The book is well written. In my reading I did not notice grammatical errors.

For this subject and in the examples given, I did not notice any cultural issues.

For the field of social work where qualitative data is as common as quantitative, the importance of giving students the rationale or the motivation to learn the quantitative side is understated. To use this text as an introductory statistics OER textbook in a social work curriculum, the instructor will want to bring in field-relevant examples to engage and motivate students. The field needs data-driven decision making and evidence-based practices to become more ubiquitous than not. Preparing future social workers by teaching introductory statistics is essential to meet that goal.

Reviewed by Mamata Marme, Assistant Professor, Augustana College on 6/25/19

This textbook offers a fairly comprehensive summary of what should be discussed in an introductory course in Statistics. The statistical literacy exercises are particularly interesting. It would be helpful to have the statistical tables... read more

Comprehensiveness rating: 4 see less

This textbook offers a fairly comprehensive summary of what should be discussed in an introductory course in Statistics. The statistical literacy exercises are particularly interesting. It would be helpful to have the statistical tables attached in the same package, even though they are available online.

The terminology and notation used in the textbook is pretty standard. The content is accurate.

The statistical literacy example are up to date but will need to be updated fairly regularly to keep the textbook fresh. The applications within the chapter are accessible and can be used fairly easily over a couple of editions.

The textbook does not necessarily explain the derivation of some of the formulae and this will need to be augmented by the instructor in class discussion. What is beneficial is that there are multiple ways that a topic is discussed using graphs, calculations and explanations of the results. Statistics textbooks have to cover a wide variety of topics with a fair amount of depth. To do this concisely is difficult. There is a fine line between being concise and clear, which this textbook does well, and being somewhat dry. It may be up to the instructor to bring case studies into the readings we are going through the topics rather than wait until the end of the chapter.

The textbook uses standard notation and terminology. The heading section of each chapter is closely tied to topics that are covered. The end of chapter problems and the statistical literacy applications are closely tied to the material covered.

The authors have done a good job treating each chapter as if they stand alone. The lack of connection to a past reference may create a sense of disconnect between the topics discussed

The text's "modularity" does make the flow of the material a little disconnected. If would be better if there was accountability of what a student should already have learnt in a different section. The earlier material is easy to find but not consistently referred to in the text.

I had no problem with the interface. The online version is more visually interesting than the pdf version.

I did not see any grammatical errors.

Cultural Relevance rating: 4

I am not sure how to evaluate this. The examples are mostly based on the American experience and the data alluded to mostly domestic. However, I am not sure if that creates a problem in understanding the methodology.

Overall, this textbook will cover most of the topics in a survey of statistics course.

Reviewed by Alexandra Verkhovtseva, Professor, Anoka-Ramsey Community College on 6/3/19

This is a comprehensive enough text, considering that it is not easy to create a comprehensive statistics textbook. It is suitable for an introductory statistics course for non-math majors. It contains twenty-one chapters, covering the wide range... read more

This is a comprehensive enough text, considering that it is not easy to create a comprehensive statistics textbook. It is suitable for an introductory statistics course for non-math majors. It contains twenty-one chapters, covering the wide range of intro stats topics (and some more), plus the case studies and the glossary.

The content is pretty accurate, I did not find any biases or errors.

The book contains fairly recent data presented in the form of exercises, examples and applications. The topics are up-to-date, and appropriate technology is used for examples, applications, and case studies.

The language is simple and clear, which is a good thing, since students are usually scared of this class, and instructors are looking for something to put them at ease. I would, however, try to make it a little more interesting, exciting, or may be even funny.

Consistency is good, the book has a great structure. I like how each chapter has prerequisites and learner outcomes, this gives students a good idea of what to expect. Material in this book is covered in good detail.

The text can be easily divided into sub-sections, some of which can be omitted if needed. The chapter on regression is covered towards the end (chapter 14), but part of it can be covered sooner in the course.

The book contains well organized chapters that makes reading through easy and understandable. The order of chapters and sections is clear and logical.

The online version has many functions and is easy to navigate. This book also comes with a PDF version. There is no distortion of images or charts. The text is clean and clear, the examples provided contain appropriate format of data presentation.

No grammatical errors found.

The text uses simple and clear language, which is helpful for non-native speakers. I would include more culturally-relevant examples and case studies. Overall, good text.

In all, this book is a good learning experience. It contains tools and techniques that free and easy to use and also easy to modify for both, students and instructors. I very much appreciate this opportunity to use this textbook at no cost for our students.

Reviewed by Dabrina Dutcher, Assistant Professor, Bucknell University on 3/4/19

This is a reasonably thorough first-semester statistics book for most classes. It would have worked well for the general statistics courses I have taught in the past but is not as suitable for specialized introductory statistics courses for... read more

This is a reasonably thorough first-semester statistics book for most classes. It would have worked well for the general statistics courses I have taught in the past but is not as suitable for specialized introductory statistics courses for engineers or business applications. That is OK, they have separate texts for that! The only sections that feel somewhat light in terms of content are the confidence intervals and ANOVA sections. Given that these topics are often sort of crammed in at the end of many introductory classes, that might not be problematic for many instructors. It should also be pointed out that while there are a couple of chapters on probability, this book spends presents most formulas as "black boxes" rather than worry about the derivation or origin of the formulas. The probability sections do not include any significant combinatorics work, which is sometimes included at this level.

I did not find any errors in the formulas presented but I did not work many end-of-chapter problems to gauge the accuracy of their answers.

There isn't much changing in the introductory stats world, so I have no concerns about the book becoming outdated rapidly. The examples and problems still feel relevant and reasonably modern. My only concern is that the statistical tool most often referenced in the book are TI-83/84 type calculators. As students increasingly buy TI-89s or Inspires, these sections of the book may lose relevance faster than other parts.

Solid. The book gives a list of key terms and their definitions at the end of each chapter which is a nice feature. It also has a formula review at the end of each chapter. I can imagine that these are heavily used by students when studying! Formulas are easy to find and read and are well defined. There are a few areas that I might have found frustrating as a student. For example, the explanation for the difference in formulas for a population vs sample standard deviation is quite weak. Again, this is a book that focuses on sort of a "black-box" approach but you may have to supplement such sections for some students.

I did not detect any problems with inconsistent symbol use or switches in terminology.

Modularity rating: 3

This low rating should not be taken as an indicator of an issue with this book but would be true of virtually any statistics book. Different books still use different variable symbols even for basic calculated statistics. So trying to use a chapter of this book without some sort of symbol/variable cheat-sheet would likely be frustrating to the students.

However, I think it would be possible to skip some chapters or use the chapters in a different order without any loss of functionality.

This book uses a very standard order for the material. The chapter on regressions comes later than it does in some texts but it doesn't really matter since that chapter never seems to fit smoothly anywhere.

There are numerous end of chapter problems, some with answers, available in this book. I'm vacillating on whether these problems would be more useful if they were distributed after each relevant section or are better clumped at the end of the whole chapter. That might be a matter of individual preference.

I did not detect any problems.

I found no errors. However, there were several sections where the punctuation seemed non-ideal. This did not affect the over-all useability of the book though

I'm not sure how well this book would work internationally as many of the examples contain domestic (American) references. However, I did not see anything offensive or biased in the book.

Reviewed by Ilgin Sager, Assistant Professor, University of Missouri - St. Louis on 1/14/19

As the title implies, this is a brief introduction textbook. It covers the fundamental of the introductory statistics, however not a comprehensive text on the subject. A teacher can use this book as the sole text of an introductory statistics.... read more

As the title implies, this is a brief introduction textbook. It covers the fundamental of the introductory statistics, however not a comprehensive text on the subject. A teacher can use this book as the sole text of an introductory statistics. The prose format of definitions and theorems make theoretical concepts accessible to non-math major students. The textbook covers all chapters required in this level course.

It is accurate; the subject matter in the examples to be up to date, is timeless and wouldn't need to be revised in future editions; there is no error except a few typographical errors. There are no logic errors or incorrect explanations.

This text will remain up to date for a long time since it has timeless examples and exercises, it wouldn't be outdated. The information is presented clearly with a simple way and the exercises are beneficial to follow the information.

The material is presented in a clear, concise manner. The text is easy readable for the first time statistics student.

The structure of the text is very consistent. Topics are presented with examples, followed by exercises. Problem sets are appropriate for the level of learner.

When the earlier matters need to be referenced, it is easy to find; no trouble reading the book and finding results, it has a consistent scheme. This book is set very well in sections.

The text presents the information in a logical order.

The learner can easily follow up the material; there is no interface problem.

There is no logic errors and incorrect explanations, a few typographical errors is just to be ignored.

Not applicable for this textbook.

Reviewed by Suhwon Lee, Associate Teaching Professor, University of Missouri on 6/19/18

This book is pretty comprehensive for being a brief introductory book. This book covers all necessary content areas for an introduction to Statistics course for non-math majors. The text book provides an effective index, plenty of exercises,... read more

This book is pretty comprehensive for being a brief introductory book. This book covers all necessary content areas for an introduction to Statistics course for non-math majors. The text book provides an effective index, plenty of exercises, review questions, and practice tests. It provides references and case studies. The glossary and index section is very helpful for students and can be used as a great resource.

Content appears to be accurate throughout. Being an introductory book, the book is unbiased and straight to the point. The terminology is standard.

The content in textbook is up to date. It will be very easy to update it or make changes at any point in time because of the well-structured contents in the textbook.

The author does a great job of explaining nearly every new term or concept. The book is easy to follow, clear and concise. The graphics are good to follow. The language in the book is easily understandable. I found most instructions in the book to be very detailed and clear for students to follow.

Overall consistency is good. It is consistent in terms of terminology and framework. The writing is straightforward and standardized throughout the text and it makes reading easier.

The authors do a great job of partitioning the text and labeling sections with appropriate headings. The table of contents is well organized and easily divisible into reading sections and it can be assigned at different points within the course.

Organization/Structure/Flow rating: 4

Overall, the topics are arranged in an order that follows natural progression in a statistics course with some exception. They are addressed logically and given adequate coverage.

The text is free of any issues. There are no navigation problems nor any display issues.

The text contains no grammatical errors.

The text is not culturally insensitive or offensive in any way most of time. Some examples might need to consider citing the sources or use differently to reflect current inclusive teaching strategies.

Overall, it's well-written and good recourse to be an introduction to statistical methods. Some materials may not need to be covered in an one-semester course. Various examples and quizzes can be a great recourse for instructor.

Reviewed by Jenna Kowalski, Mathematics Instructor, Anoka-Ramsey Community College on 3/27/18

The text includes the introductory statistics topics covered in a college-level semester course. An effective index and glossary are included, with functional hyperlinks. read more

The text includes the introductory statistics topics covered in a college-level semester course. An effective index and glossary are included, with functional hyperlinks.

Content Accuracy rating: 3

The content of this text is accurate and error-free, based on a random sampling of various pages throughout the text. Several examples included information without formal citation, leading the reader to potential bias and discrimination. These examples should be corrected to reflect current values of inclusive teaching.

The text contains relevant information that is current and will not become outdated in the near future. The statistical formulas and calculations have been used for centuries. The examples are direct applications of the formulas and accurately assess the conceptual knowledge of the reader.

The text is very clear and direct with the language used. The jargon does require a basic mathematical and/or statistical foundation to interpret, but this foundational requirement should be met with course prerequisites and placement testing. Graphs, tables, and visual displays are clearly labeled.

The terminology and framework of the text is consistent. The hyperlinks are working effectively, and the glossary is valuable. Each chapter contains modules that begin with prerequisite information and upcoming learning objectives for mastery.

The modules are clearly defined and can be used in conjunction with other modules, or individually to exemplify a choice topic. With the prerequisite information stated, the reader understands what prior mathematical understanding is required to successfully use the module.

The topics are presented well, but I recommend placing Sampling Distributions, Advanced Graphs, and Research Design ahead of Probability in the text. I think this rearranged version of the index would better align with current Introductory Statistics texts. The structure is very organized with the prerequisite information stated and upcoming learner outcomes highlighted. Each module is well-defined.

Adding an option of returning to the previous page would be of great value to the reader. While progressing through the text systematically, this is not an issue, but when the reader chooses to skip modules and read select pages then returning to the previous state of information is not easily accessible.

No grammatical errors were found while reviewing select pages of this text at random.

Cultural Relevance rating: 3

Several examples contained data that were not formally cited. These examples need to be corrected to reflect current inclusive teaching strategies. For example, one question stated that “while men are XX times more likely to commit murder than women, …” This data should be cited, otherwise the information can be interpreted as biased and offensive.

An included solutions manual for the exercises would be valuable to educators who choose to use this text.

Reviewed by Zaki Kuruppalil, Associate Professor, Ohio University on 2/1/18

This is a comprehensive book on statistical methods, its settings and most importantly the interpretation of the results. With the advent of computers and software’s, complex statistical analysis can be done very easily. But the challenge is the... read more

This is a comprehensive book on statistical methods, its settings and most importantly the interpretation of the results. With the advent of computers and software’s, complex statistical analysis can be done very easily. But the challenge is the knowledge of how to set the case, setting parameters (for example confidence intervals) and knowing its implication on the interpretation of the results. If not done properly this could lead to deceptive inferences, inadvertently or purposely. This book does a great job in explaining the above using many examples and real world case studies. If you are looking for a book to learn and apply statistical methods, this is a great one. I think the author could consider revising the title of the book to reflect the above, as it is more than just an introduction to statistics, may be include the word such as practical guide.

The contents of the book seems accurate. Some plots and calculations were randomly selected and checked for accuracy.

The book topics are up to date and in my opinion, will not be obsolete in the near future. I think the smartest thing the author has done is, not tied the book with any particular software such as minitab or spss . No matter what the software is, standard deviation is calculated the same way as it is always. The only noticeable exception in this case was using the Java Applet for calculating Z values in page 261 and in page 416 an excerpt of SPSS analysis is provided for ANOVA calculations.

The contents and examples cited are clear and explained in simple language. Data analysis and presentation of the results including mathematical calculations, graphical explanation using charts, tables, figures etc are presented with clarity.

Terminology is consistant. Framework for each chapter seems consistent with each chapter beginning with a set of defined topics, and each of the topic divided into modules with each module having a set of learning objectives and prerequisite chapters.

The text book is divided into chapters with each chapter further divided into modules. Each of the modules have detailed learning objectives and prerequisite required. So you can extract a portion of the book and use it as a standalone to teach certain topics or as a learning guide to apply a relevant topic.

Presentation of the topics are well thought and are presented in a logical fashion as if it would be introduced to someone who is learning the contents. However, there are some issues with table of contents and page numbers, for example chapter 17 starts in page 597 not 598. Also some tables and figures does not have a number, for instance the graph shown in page 114 does not have a number. Also it would have been better if the chapter number was included in table and figure identification, for example Figure 4-5 . Also in some cases, for instance page 109, the figures and titles are in two different pages.

No major issues. Only suggestion would be, since each chapter has several modules, any means such as a header to trace back where you are currently, would certainly help.

Grammatical Errors rating: 4

Easy to read and phrased correctly in most cases. Minor grammatical errors such as missing prepositions etc. In some cases the author seems to have the habbit of using a period after the decimal. For instance page 464, 467 etc. For X = 1, Y' = (0.425)(1) + 0.785 = 1.21. For X = 2, Y' = (0.425)(2) + 0.785 = 1.64.

However it contains some statements (even though given as examples) that could be perceived as subjective, which the author could consider citing the sources. For example from page 11: Statistics include numerical facts and figures. For instance: • The largest earthquake measured 9.2 on the Richter scale. • Men are at least 10 times more likely than women to commit murder. • One in every 8 South Africans is HIV positive. • By the year 2020, there will be 15 people aged 65 and over for every new baby born.

Solutions for the exercises would be a great teaching resource to have

Reviewed by Randy Vander Wal, Professor, The Pennsylvania State University on 2/1/18

As a text for an introductory course, standard topics are covered. It was nice to see some topics such as power, sampling, research design and distribution free methods covered, as these are often omitted in abbreviated texts. Each module... read more

As a text for an introductory course, standard topics are covered. It was nice to see some topics such as power, sampling, research design and distribution free methods covered, as these are often omitted in abbreviated texts. Each module introduces the topic, has appropriate graphics, illustration or worked example(s) as appropriate and concluding with many exercises. An instructor’s manual is available by contacting the author. A comprehensive glossary provides definitions for all the major terms and concepts. The case studies give examples of practical applications of statistical analyses. Many of the case studies contain the actual raw data. To note is that the on-line e-book provides several calculators for the essential distributions and tests. These are provided in lieu of printed tables which are not included in the pdf. (Such tables are readily available on the web.)

The content is accurate and error free. Notation is standard and terminology is used accurately, as are the videos and verbal explanations therein. Online links work properly as do all the calculators. The text appears neutral and unbiased in subject and content.

The text achieves contemporary relevance by ending each section with a Statistical Literacy example, drawn from contemporary headlines and issues. Of course, the core topics are time proven. There is no obvious material that may become “dated”.

The text is very readable. While the pdf text may appear “sparse” by absence varied colored and inset boxes, pictures etc., the essential illustrations and descriptions are provided. Meanwhile for this same content the on-line version appears streamlined, uncluttered, enhancing the value of the active links. Moreover, the videos provide nice short segments of “active” instruction that are clear and concise. Despite being a mathematical text, the text is not overly burdened by formulas and numbers but rather has “readable feel”.

This terminology and symbol use are consistent throughout the text and with common use in the field. The pdf text and online version are also consistent by content, but with the online e-book offering much greater functionality.

The chapters and topics may be used in a selective manner. Certain chapters have no pre-requisite chapter and in all cases, those required are listed at the beginning of each module. It would be straightforward to select portions of the text and reorganize as needed. The online version is highly modular offering students both ease of navigation and selection of topics.

Chapter topics are arranged appropriately. In an introductory statistics course, there is a logical flow given the buildup to the normal distribution, concept of sampling distributions, confidence intervals, hypothesis testing, regression and additional parametric and non-parametric tests. The normal distribution is central to an introductory course. Necessary precursor topics are covered in this text, while its use in significance and hypothesis testing follow, and thereafter more advanced topics, including multi-factor ANOVA.

Each chapter is structured with several modules, each beginning with pre-requisite chapter(s), learning objectives and concluding with Statistical Literacy sections providing a self-check question addressing the core concept, along with answer, followed by an extensive problem set. The clear and concise learning objectives will be of benefit to students and the course instructor. No solutions or answer key is provided to students. An instructor’s manual is available by request.

The on-line interface works well. In fact, I was pleasantly surprised by its options and functionality. The pdf appears somewhat sparse by comparison to publisher texts, lacking pictures, colored boxes, etc. But the on-line version has many active links providing definitions and graphic illustrations for key terms and topics. This can really facilitate learning as making such “refreshers” integral to the new material. Most sections also have short videos that are professionally done, with narration and smooth graphics. In this way, the text is interactive and flexible, offering varied tools for students. To note is that the interactive e-book works for both IOS and OS X.

The text in pdf form appeared to free of grammatical errors, as did the on-line version, text, graphics and videos.

This text contains no culturally insensitive or offensive content. The focus of the text is on concepts and explanation.

The text would be a great resource for students. The full content would be ambitious for a 1-semester course, such use would be unlikely. The text is clearly geared towards students with no statistics background nor calculus. The text could be used in two styles of course. For 1st year students early chapters on graphs and distributions would be the starting point, omitting later chapters on Chi-square, transformations, distribution-free and size effect chapters. Alternatively, for upper level students the introductory chapters could be bypassed with the latter chapters then covered to completion.

This text adopts a descriptive style of presentation with topics well and fully explained, much like the “Dummy series”. For this, it may seem a bit “wordy”, but this can well serve students and notably it complements powerpoint slides that are generally sparse on written content. This text could be used as the primary text, for regular lectures, or as reference for a “flipped” class. The e-book videos are an enabling tool if this approach is adopted.

Reviewed by David jabon, Associate Professor, DePaul University on 8/15/17

This text covers all the standard topics in a semester long introductory course in statistics. It is particularly well indexed and very easy to navigate. There is comprehensive hyperlinked glossary. read more

This text covers all the standard topics in a semester long introductory course in statistics. It is particularly well indexed and very easy to navigate. There is comprehensive hyperlinked glossary.

The material is completely accurate. There are no errors. The terminology is standard with one exception: the book calls what most people call the interquartile range, the H-spread in a number of places. Ideally, the term "interquartile range" would be used in place of every reference to "H-spread." "Interquartile range" is simply a better, more descriptive term of the concept that it describes. It is also more commonly used nowadays.

This book came out a number of years ago, but the material is still up to date. Some more recent case studies have been added.

The writing is very clear. There are also videos for almost every section. The section on boxplots uses a lot of technical terms that I don't find are very helpful for my students (hinge, H-spread, upper adjacent value).

The text is internally consistent with one exception that I noted (the use of the synonymous words "H-spread" and "interquartile range").

The text book is brokenly into very short sections, almost to a fault. Each section is at most two pages long. However at the end of each of these sections there are a few multiple choice questions to test yourself. These questions are a very appealing feature of the text.

The organization, in particular the ordering of the topics, is rather standard with a few exceptions. Boxplots are introduced in Chapter II before the discussion of measures of center and dispersion. Most books introduce them as part of discussion of summaries of data using measure of center and dispersion. Some statistics instructors may not like the way the text lumps all of the sampling distributions in a single chapter (sampling distribution of mean, sampling distribution for the difference of means, sampling distribution of a proportion, sampling distribution of r). I have tried this approach, and I now like this approach. But it is a very challenging chapter for students.

The book's interface has no features that distracted me. Overall the text is very clean and spare, with no additional distracting visual elements.

The book contains no grammatical errors.

The book's cultural relevance comes out in the case studies. As of this writing there are 33 such case studies, and they cover a wide range of issues from health to racial, ethnic, and gender disparity.

Each chapter as a nice set of exercises with selected answers. The thirty three case studies are excellent and can be supplement with some other online case studies. An instructor's manual and PowerPoint slides can be obtained by emailing the author. There are direct links to online simulations within the text. This text is very high quality textbook in every way.

Table of Contents

• 1. Introduction
• 2. Graphing Distributions
• 3. Summarizing Distributions
• 4. Describing Bivariate Data
• 5. Probability
• 6. Research Design
• 7. Normal Distributions
• 8. Advanced Graphs
• 9. Sampling Distributions
• 10. Estimation
• 11. Logic of Hypothesis Testing
• 12. Testing Means
• 14. Regression
• 15. Analysis of Variance
• 16. Transformations
• 17. Chi Square
• 18. Distribution-Free Tests
• 19. Effect Size
• 20. Case Studies
• 21. Glossary

Ancillary Material

• Ancillary materials are available by contacting the author or publisher .

About the Book

Introduction to Statistics is a resource for learning and teaching introductory statistics. This work is in the public domain. Therefore, it can be copied and reproduced without limitation. However, we would appreciate a citation where possible. Please cite as: Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University. Instructor's manual, PowerPoint Slides, and additional questions are available.

About the Contributors

David Lane is an Associate Professor in the Departments of Psychology, Statistics, and Management at the Rice University. Lane is the principal developer of this resource although many others have made substantial contributions. This site was developed at Rice University, University of Houston-Clear Lake, and Tufts University.

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Statistics for applications, lecture 1: introduction to statistics.

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LESSON 1. INTRODUCTION TO STATISTICS

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• Preferences

Introduction to Statistics - PowerPoint PPT Presentation

• Introduction to Statistics

Introduction to Statistics 1.1 An Overview of Statistics 1.2 Data Classification 1.3 Experimental Design * Larson/Farber 4th ed. Methods of Collecting Data ... – PowerPoint PPT presentation

• 1.1 An Overview of Statistics
• 1.2 Data Classification
• 1.3 Experimental Design
• An Overview of Statistics
• Classifying Data
• Critical Thinking
• The science of collecting, organizing, analyzing, and interpreting data in order to make decisions.
• 1. HCC is doing a study on how many credit hours a HCC student is taking.
• 2. HCC is doing a study on many hours a week a HCC student is working.
• A fashion magazine gathers data on the price of womens jeans.
• The responses, counts, measurements, or observations that have been collected.
• Data can be classified as one of 2 types
• Qualitative Data Consists of non-numeric, categorical attributes or labels
• Quantitative data Numerical measurements or counts.
• Discrete data finite number of possible data values 0, 1, 2, 3, 4.
• ex Number of classes a student is taking
• A number that describes some characteristic of an entire population.
• Average age of all people in the United States
• Ex Parameters vs. Statistics
• The average credit load of all HCC full-time students is 14.2 credit hours.
• From a sample of 300 HCC full-time students showed the average work hours a week is 18.3 hours.
• A gallup poll of 1012 adults nationwide showed 34 owned a handgun.
• Decide which part of the study represents the descriptive branch of statistics. What conclusions might be drawn from the study using inferential statistics?
• Almost all fields of study benefit from the application of statistical methods
• Statistics often lead to change
• Bad Samples
• Small Samples
• Misleading Graphs
• Pictographs
• Loaded Questions
• Correlation Causality
• Self Interest Study
• Samples must be unbiased and fairly represent the entire population.
• If the data is not collected appropriately, the data may be completely useless. Garbage in, garbage out
• Voluntary response sample Respondents themselves decide whether to be included in the sample
• Ex. Online surveys
• Ex. Ratemyprofessor.com
• Experimental Design
• What is it you want to study?
• What is the population to gather data from?
• Collect data. If you use a sample, it must be representative of the population.
• Descriptive Statistics organize, present, summarize data
• Inferential Statistics draw conclusions about the population based on sample data
• The sample must be unbiased and fairly represent the entire population.
• Want the maximum information at the minimum cost. What sample size is needed?
• Observational study
• A researcher observes or measures characteristics of interest of part of a population but does not change any existing conditions.
• A treatment is applied to part of a population and responses are observed.
• An investigation of one or more characteristics of a population, usually be asking people questions.
• Commonly done by interview, mail, or telephone.
• Uses a mathematical or physical model to reproduce the conditions of a situation or process. Often involves the use of computers.
• Consider the following studies. Which method of data collection would you use to collect data for each study?
• A study of salaries of NFL players.
• A study of the emergency response times during a terrorist attack.
• A study of whether changing teaching techniques improves FCAT scores.
• A study of whether Tampa residents support a mass transit system.
• Random versus Non-Random Samples
• Convenience Samples
• Simple Random Samples
• Systematic Samples
• Cluster Samples
• Random Sampling
• Every member of the population has an equal change of being selected.
• Non-Random Sampling
• Some members of the population have no chance of being picked. Often leads to biased samples.
• Data is collected that is readily available and easy to get.
• Self-selected surveys or voluntary response surveys (online surveys, magazine surveys, 1-800-Verdict, Ratemyprofessor.com)
• A random sample where every member of the population and every group of the same size has an equal chance of being selected.
• Usually involves using a random number generator.
• Number each element of the population from 1 to N.
• Use a random number generator (table, calculator, computer) to randomly selected a sample of size n.
• TI-83/4 randint (1,N,n), or
• Table 1 in text. Pick a random start.
• Choose a starting value at random. Then
• choose every kth member of the population.
• example Select every 3rd patient who enters the ER.
• Divide a population into at least 2 different subgroups (strata) that share the same characteristics (age, gender, ethnicity, income, etc) and select a random sample from each group.
• Advantages More information
• Divide the population into many like subgroups (clusters) randomly select some of those clusters, and then select all of the members of those clusters to be in the sample.
• Advantage geographically separately populations
• Sampling Error
• the expected difference between a sample result and the true population result. (e.g. Margin of error).
• Non-Sampling Error
• sample data is incorrectly gathered, collected, or recorded.
• Selection Bias - bad sample
• Response Bias- bad data incorrect responses, inaccurate measurements,

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• Department for Energy Security & Net Zero

Summary of the Green Homes Grant Local Authority Delivery (LAD) and Home Upgrade Grant (HUG) statistics: September 2024

Published 26 September 2024

Applies to England

© Crown copyright 2024

This publication is licensed under the terms of the Open Government Licence v3.0 except where otherwise stated. To view this licence, visit nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: [email protected] .

Where we have identified any third party copyright information you will need to obtain permission from the copyright holders concerned.

This publication is available at https://www.gov.uk/government/statistics/green-homes-grant-local-authority-delivery-lad-and-home-upgrade-grant-hug-release-september-2024/summary-of-the-green-homes-grant-local-authority-delivery-lad-and-home-upgrade-grant-hug-statistics-september-2024

Introduction

The Home Upgrade Grant (HUG) and Local Authority Delivery scheme (LAD) are government schemes supporting energy efficiency upgrades of low-energy efficiency (EPC of D or lower) low-income (household income below £30k) households across England.

HUG Phase 2 (HUG 2) is actively reporting and has allocated £630 million for delivery between September 2023 and March 2025. HUG 2 is exclusively for off-gas-grid properties.

LAD Phases 1 and 2 previously received £500 million between them. These schemes ran between 2020-2022. LAD Phase 3 made £287 million of funding available for Local Authorities. HUG 1 allocated £220 million, exclusively for homes that are off the gas grid. Both schemes ran from 2022-2023.

• Delivery by Scheme as of August 2024 Statistics Release

What you need to know about these statistics

The data contained in these statistics is based on returns submitted by mid-September 2024, covering measures delivered to the end of July 2024.

All figures in this publication are provisional and subject to revision. For more information, see the Department’s statistical revisions policy .

From this release onwards, data presented at the parliamentary constituency level are based on the new Westminster Parliamentary Constituencies that came into effect on 4 July 2024. Data will no longer be presented using the previous boundaries. Comments on this from users of these statistics should be sent to [email protected] .

Key statistics

Total homes upgraded.

• This publication is based on returns submitted in mid-September, covering measures installed to the end of July 2024, with preliminary August data included for completeness. HUG 2 has installed around 5,300 measures across 3,000 households to date, including some initial data for August. There were 720 measures installed and 400 upgraded households reported in July.
• Across all schemes (LAD 1, LAD 2, LAD 3, HUG 1, and HUG 2) there were 89,400 measures installed in 65,500 households, based on data reported to the end of August 2024.
• The average Energy Performance Certificate (EPC) improved by 1 band for HUG 2, with 58% of homes upgraded to EPC C or higher. These figures are based on the 96% of households that reported pre and post installation EPC scores.

Figure 1: Cumulative number of homes upgraded by HUG 2

The data used in this chart can be found in Table 3 of the accompanying tables .

Homes upgraded by month

• HUG 2 received notice of 400 homes upgraded in July compared to 420 homes in June and 350 homes in May. There was a similar pattern in measures installed, with 720 installations reported in July, compared to 750 installations in June and 590 in May. In total, HUG 2 has delivered 5,300 measures across 3,000 households, including preliminary data for July.
• Figure 2 shows the monthly number of homes upgraded across all phases of LAD and HUG: all LAD phases show the same pattern of starting slowly (hundreds of homes a month), before ramping up to upgrade several thousand homes per month. HUG 1 followed a similar pattern, but peaked at around 700 homes upgraded per month. HUG 2 has so far reached around 420 homes upgraded per month. LAD 1 and 2 had a small number of homes upgraded after the official scheme ended in September 2022, which are not shown in the figure.

Figure 2: Number of Homes Upgraded by Month

Delivery by measure type

• Across HUG 2, solar PV was the most common type of measure, accounting for 35% of HUG 2 installations. Insulation accounted for around 29% of HUG 2 measures followed by Low Carbon Heat (27%) as shown in Figure 3. Other LCH includes all other forms of low carbon heating not listed. Other Insulation includes all other insulation measures not listed.

Figure 3: Type of Measures Installed in HUG 2

The data used in this chart can be found in Table 1.5 of the accompanying tables .

Delivery by region

• The South East region has the most homes upgraded through HUG 2 (29% of total HUG 2 measures), with the East (23%) and North West (21%) also containing a higher proportion of homes upgraded. The South West (13%) and Yorkshire and Humber (9%) had smaller numbers of homes upgraded. No other region received more than 2% of HUG 2 homes upgraded. Please note the regions have significantly different populations and participating grant recipients.

Annex: Further Information

Next publication date.

The next publication will be at 09:30am on Thursday 31st October 2024.

Scheme Information

More information on the HUG and LAD schemes can be found on the Department’s website .

Accompanying tables

Tables showing number of measures installed and households upgraded under HUG and LAD are available online. The tables also contain information on methodology and data quality.

Revisions policy

The  Department’s statistical revisions policy  sets out the revisions policy for these statistics, which has been developed in accordance with the UK Statistics Authority  Code of Practice for Statistics .

User engagement

Users are encouraged to provide comments and feedback on how these statistics are used and how well they meet user needs. Comments on any issues relating to this statistical release are welcomed and should be sent to:  [email protected] . The Department’s statement on  statistical public engagement and data standards  sets out the department’s commitments on public engagement and data standards as outlined by the Code of Practice for Statistics.

Pre-release access to statistics

Some ministers and officials receive access to these Official Statistics up to 24 hours before release. Details of the arrangements for doing this and a list of the ministers and officials that receive pre-release access to these statistics can be found in the  Department’s statement of compliance  with the Pre-Release Access to Official Statistics Order 2008.

Responsible statisticians: Nick Dann and Zheni Goranova

Email: [email protected]

Media enquiries: 020 7215 1000

Public enquiries: 0300 068 6838

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25 September 2024

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• Pupil attendance in schools

Introduction

These figures are derived from regular data automatically submitted to the Department for Education (DfE) by participating schools. The data is submitted on a daily basis and includes the attendance codes (opens in a new tab) for each pupil on their registers during the morning and afternoon sessions.

Figures relate to the attendance of 5 to 15 year old (i.e. compulsory school age) pupils in state-funded primary, secondary and special schools in England.

This release covers the 2024/25 academic year from 09 September to 13 September 2024. National level figures are included in underlying data for the week commencing 02 September 2024. For the full 2023/24 academic year and termly pupil absence data, including by characteristics please see this historical publication .

The figures are published as official statistics in development to give an indicative figure for the absence rate during the 2024/25 academic year. The pupil attendance dashboard (opens in a new tab) will be updated fortnightly, providing aggregate metrics on overall absence and reasons for absence estimated at national, regional and local authority level only. Due to the timeliness of the data and that they are based on a subset of schools, figures are estimates that we expect to change as registers are adjusted. They should be viewed as an early indicator for the more detailed but less regular Accredited Official Statistics on pupil absence (which include school level breakdowns). The Accredited Official Statistics are updated termly, with the latest data published in August 2024 relating to the Autumn term 2023/24, including data on characteristics.

From the start of the 2024/25 academic year, it became mandatory for schools to share attendance data (opens in a new tab) with the DfE. If you are a school that is not already sharing your daily attendance data, you need to approve this in your Wonde portal. This will also give you, your local authority and your multi-academy trust (if applicable)  access to daily attendance reports (opens in a new tab)  to help identify pupils needing attendance support earlier.

Headline facts and figures - 2024

This release covers the 2024/25 academic year between 09 and 13 September 2024. 

The attendance rate (proportion of possible sessions attended) was 95.2% across all schools in the week commencing 09 September 2024 . The absence rate was, therefore, 4.8% across all schools.

By school type, the absence rates across the week commencing 09 September 2024 were:

• 3.8% in state-funded primary schools (2.3% authorised and 1.5% unauthorised)
• 5.7% in state-funded secondary schools (3.1% authorised and 2.6% unauthorised)
• 10.1% in state-funded special schools (7.0% authorised and 3.1% unauthorised)

Absence was 0.2 percentage points lower across all schools in the week commencing 09 September 2024 than in the equivalent week in the last academic year ( week commencing 11 September 2023 ). This has been driven equally by a 0.1 percentage point decrease in both authorised and unauthorised absence.

High-level national figures for the week commencing 2 September 2024 (first week back) are available in the data catalogue below. For the full 2023/24 academic year and termly pupil absence data, including by characteristics please see this historical publication .

Explore data and files used in this release

View or create your own tables.

View tables that we have built for you, or create your own tables from open data using our table tool

Data catalogue

Browse and download open data files from this release in our data catalogue

Data guidance

Learn more about the data files used in this release using our online guidance

Download all data (ZIP)

Download all data available in this release as a compressed ZIP file

View related dashboard(s)

Access the Pupil attendance and absence in schools in England: data dashboard (opens in a new tab) (opens in a new tab) here

The pupil attendance dashboard (opens in a new tab) (opens in a new tab) is updated fortnightly. The latest data relates to the week commencing 09 September 2024. The dashboard displays attendance and absence headline figures, and reasons for absence at national, regional and local authority geographic levels. Data is available across state-funded primary, secondary and special schools and can be broken down by individual school type.

Underlying data is available within the “Explore data and files” section of this page, under the data catalogue.

Latest data - week commencing 09 September 2024

The latest data relates to the week commencing 09 September 2024 and is available in the pupil attendance dashboard (opens in a new tab) . Data is collected on a daily basis and data for the interim weeks between publications is included in year-to-date figures and is available on a daily and weekly basis in the underlying data available on this page (see “Explore data and files”). The dashboard displays attendance and absence headline figures, and reasons for absence at national, regional and local authority geographic levels. Data is available across primary, secondary and special schools and can be broken down by individual school type.

The data shows that the attendance rate across the week for all schools was 95.2%, giving an overall absence rate of 4.8%. The absence rate varied across the week with a low of 4.5% on Wednesday, and a peak of 5.5% on Friday. The peak in absence on a Friday is in line with weekly patterns in historical attendance data .

Users should be aware of the following: Response rate - 96% of schools shared data in the most recent week, therefore national figures are estimates. Across school types this was: 96% of state-funded primary schools, 97% of state-funded secondary schools and 92% of state-funded special schools. This follows it becoming mandatory for schools to share attendance data with the DfE from the start of the 2024/25 academic year. This response rate is in line with the level of response seen at the end of the 2023/24 academic year (95%), therefore there is no discontinuity in the series. However, please note that the response rate was lower in the equivalent week at the start of the 2023/24 academic year (85%) therefore comparisons to this time point should be made with awareness of the difference in data coverage.  Estimates for non-response - In recognition that response rates are not equal across school types and, therefore, not representative of the total school population, the total rates for all schools have been weighted based on the Spring 2024 school census. Reporting lag - Schools update their registers continually and attendance codes change, resulting in absence rates for particular days to decrease over time. Analysis of data from the Summer 2022 term suggests that this could be a decrease in the absence rate of around 1 percentage point before settling down. Historical figures from week 37 onwards will be recalculated in each publication.

From the start of the 2024/25 academic year, it became mandatory for schools to share attendance data (opens in a new tab) with the DfE. If you are a school that is not already sharing your daily attendance data, you need to approve this in your Wonde portal. This will also give you, your local authority and your multi-academy trust (if applicable) access to daily attendance reports (opens in a new tab) to help identify pupils needing attendance support earlier.

First week of the 2024/25 academic year

Attendance and absence rates by day and school type for the week commencing 02 September 2024 are available in the data catalogue. In recognition of the uncertainty around inset days, reporting lag and reduced response rate, rates have been rounded to 0 decimal places.

Users should be aware of the following: Response rate - The lower response rates reflect how some schools operate inset days on their first days back and may not have turned on their school registers. Overall, the response rate on Monday 02 September was 45%, and 96% on Friday 06 September. In recognition that response rates are not equal across school types and, therefore, not representative of the total school population, the overall attendance and absence figure for total schools has been weighted based on the Spring 2024 school census. Inset days and phased returns - Schools may run inset days on the first days back of a new term. Additionally, some - particularly secondary schools - may use phased returns, which see individual year groups return a day ahead of others. The data allows us to infer when schools are operating this way and the figures presented only consider pupils who were expected to attend on the day. Reporting lag - Schools update their registers continually and attendance codes change, resulting in absence rates for particular days to decrease over time.

Help and support

Methodology.

Find out how and why we collect, process and publish these statistics.

Official statistics in development

These statistics are undergoing a development. They have been developed under the guidance of the Head of Profession for Statistics and published to involve users and stakeholders at an early stage in assessing their suitability and quality.

They have been produced as far as possible in line with the Code of Practice for Statistics.

This can be broadly interpreted to mean that these statistics are:

• managed impartially and objectively in the public interest
• meet identified user needs
• produced according to sound methods
• well explained and readily accessible

Find out more about the standards we follow to produce these statistics through our Standards for official statistics published by DfE guidance .

If you have a specific enquiry about Pupil attendance in schools statistics and data:

School Census Statistics Team

Press office.

If you have a media enquiry:

Telephone: 020 7783 8300

Public enquiries

If you have a general enquiry about the Department for Education (DfE) or education:

Telephone: 037 0000 2288

Opening times: Monday to Friday from 9.30am to 5pm (excluding bank holidays)