This text covers all the topics I would want to cover in my statistics course, but there is not an index and/or glossary. I believe having an index is so important for students as they may not even know in what chapter to reference a term so the index would be invaluable for them in finding information. Psychology students often find statistics courses to be different from their other psychology classes. There are some distinct differences, especially involving study strategies for class success. The first difference is learning a new vocabulary—it is similar to learning a new language. Knowing the meaning of certain words will help as you are reading the material and working through the problems. Secondly, practice is critical for success; reading over the material is not enough. Statistics is a subject learned by doing, so make sure you work through any homework questions, chapter questions, and practice problems available. Statistical knowledge gives you a set of skills employable in graduate school and the workplace. Data science is a burgeoning field, and there is practical significance in learning this material. The statistics presented in this book are some of the most common ones used in research articles, and we hope by the end of this OER you’ll feel comfortable reading (and not skipping!) the results section of an article. This work is broken into 14 chapters, covering the fundamentals of statistics, and hypothesis testing. In addition, you'll have access to Kortext's smart study tools including highlighting, notetaking, copy and paste, and easy reference export. I don’t see any cultural bias in the text or exercises sets. Although not necessarily cultural, I like how this text is inclusive to those with color deficiencies. For example, when describing a graph with multiple colored lines, the authors also reference the position of each line on the graph. This is not only useful for those with color deficiencies but also for those who read the text on an e-reader that doesn’t have color. Organization is good and is fairly standard for the flow of a stats class. Personally, I'd prefer to start with correlation and regression, but how it is works.

Psychology Statistics For Dummies by Donncha Hanna | Goodreads Psychology Statistics For Dummies by Donncha Hanna | Goodreads

Some of the images are a bit blurry. They were still interpretable, but it was a bit distracting. Navigation was easy – especially as I read it on my e-reader – which I think will be a big benefit to students (using tablets, e-readers, PCs, or printing the text). I think the content itself is up-to-date and will not need much updating. The only pieces that may need updating are those that show how to present the results. I believe it was intended to be APA style which may require updating if the APA guidelines change. I also liked the section on misleading graphics – not always included in introductory statistics books- so it was nice to see in this text. I think knowing about data visualization techniques will be a very useful skill for all students, especially in the era of big data. I did not notice any issues with terminology -- the topics build easily from each other and use previous knowledge to help students follow along. This book focuses on calculations but does not use the computational formula for sum of squares. I think this makes it more difficult for students to avoid making computational errors and it makes the calculations more difficult. Introduction to Statistics in the Psychological Sciences provides an accessible introduction to the fundamentals of statistics, and hypothesis testing as need for psychology students. The textbook introduces the fundamentals of statistics, an introduction to hypothesis testing, and t Tests. Related samples, independent samples, analysis of variance, correlations, linear regressions and chi-squares are all covered along with expanded appendices with z, t, F correlation, and a Chi-Square table. The text includes key terms and exercises with answers to odd-numbered exercises.I am torn about the use of the X-bar to represent the sample mean. For students who will be moving on to more advanced statistics the use of X-bar would be helpful, but there is a small proportion of my students who move on to more advanced statistics. The norm in social statistics is now to use the M for the sample mean and my students may be confused as they move into the research methods lab course and are presented with M instead of X-bar.

Psychology Statistics For Dummies eBook : Hanna, Donncha

We currently use Gravetter & Walleneau and this book seems to cover nearly all of the same material. The main topic that this text does not cover is factorial ANOVA, which is an important and complex topic for undergraduates. However, our current book focuses solely on calculating Factorial ANOVA and not on interpreting main effects and interactions so I have to supplement our current book significantly, so it would not change my teaching approach. It provides the definitional formula for the standard deviation which I find more useful than other texts. Good table of contents but no index or glossary. This book seems like a very good OER option, so our current plan is adopt this text for next year. Cons: Ideally the symbols for mean and standard deviation would be the ones specified in APA format, but his text uses X bar instead of M for sample mean and S instead of SD for sample standard deviation. Only the derivation formula for sum of squares is provided, and not the computation formula. Chi square goodness-of-fit model offered in chapter assumes an equal frequency across cells, rather than matching proportions to those in a known population. The formula notation for chi-square is not what I’m used to seeing. There are no complete tables (partial tables are embedded within the chapters) – so you would need to link to another OER for that. That said, the tables are probably more appropriately placed in a particular chapter and not in the Appendix. I use a lot of “word problems” in statistics (summaries of real studies so that students can work on identifying DV, IV, writing hypotheses, in addition to computing the statistical tests. Overall there are about 10-12 end-of-chapter problems for each chapter and not many are word problems, so I will need to supplement. There are no instructor resources, test banks, etc. If you have taught statistics for awhile you have probably developed your own resources (i.e., Powerpoints, test questions, homework questions, word problems for in class exercises) but if you are just starting out this probably isn’t the OER for you. If I were going to write a statistics book, it would be very close to this. This is a readable textbook appropriate for an introductory statistics course in psychology. Examples given are succinct and easy to follow.MD5 of a better version of this file (if applicable). Fill this in if there is another file that closely matches this file (same edition, same file extension if you can find one), which people should use instead of this file. If you know of a better version of this file outside of Anna’s Archive, then please upload it.