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Psychology Statistics For Dummies

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The measures of dispersion you use in psychology statistics show you the spread or variability of the variable you are measuring. The three main ones are the range, the interquartile range, and the standard deviation. Getting to know the range, interquartile range, and standard deviation

Statistics For Dummies Cheat Sheet Statistics For Dummies Cheat Sheet

I think this text is written at an appropriate level for the target audience and appropriate context is introduced when covering technical terminology. I particularly liked the visual of the distribution balancing on a triangle to show symmetrical and asymmetrical distributions (Chapter 3). Distribution of scores: For the purposes of choosing a measure of central tendency, you need to know whether any extreme scores exist in your data set (often called outliers) or whether the distribution of scores is skewed. When you determine the level of measurement of your variable of interest and whether or not there is skewness and/or extreme scores in your data set then you can determine the most appropriate measure of central tendency, as follows: The text can be divided into smaller sections as written. It would be hard to selectively chose sections to cover and not others because of the comprehensive nature of the material. However, these chapters can be selectively used if an instructor wanted to supplement their course without adapting the entire text. I am not advocating this, as I think the text would be suitable as a whole for a course, but it is possible. In Chapter 2, there are graphs with iMacs from the 1990s. I've seen this graphic in other texts and it always throws me off because most students were not yet born when these computers were out. Also, I've found that psych stats books don't actually have examples from psychology. This book is no exception. Very few examples, if any, that I came across were from the psychological sciences.An Introduction to Psychological Statistics ( https://irl.umsl.edu/oer/4/). Garett C. Foster, University of Missouri–St. Louis. 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. 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. The is not indexed for a pdf reader making unusable for a course. Adding bookmarks to each chapter and chapter sub-sections would make the text much more usable. This textbook covers all of the material I cover in an intro psych stats class. I'd like to see a statistics software program integrated into the text - JASP or R would be great, keeping in line with being an OER.

Psychology Statistics For Dummies (Paperback) - Waterstones Psychology Statistics For Dummies (Paperback) - Waterstones

You determine the most appropriate measure of dispersion as follows, depending on the nature of your data: The book is well-written (i.e., clear, concise, engaging). It is appropriate for an undergraduate taking their first statistics course.The content in this text is already dated as there is no integration of statistical software output, which I think should be included for descriptive statistics and hypothesis testing. Using statistical software is prevalent in the workplace and academic settings so the opportunity for students to view and interpret output is important. This work was created as part of the University Libraries’ Open Educational Resources Initiative at the University of Missouri–St. Louis. Interval: If you measure a variable at the interval level of measurement, it has the measurement properties of magnitude and equal intervals. I believe the authors had a logical flow to their presentation of material. They have also designed the text (as in the above comment) in a way so that pieces can be moved around to cater to the instructor. Pros include: End-of-chapter exercises with answers to odd numbered problems, the most common measures of effect size are used (e.g., Uses Cohen’s d for z and t-tests, eta squared for ANOVA, Cramer’s V for chi-square), focus in correlations chapter is on Pearson correlation rather than Spearman (or other types of correlations) which is appropriate given that Pearson correlations are the type overwhelmingly used in psychological research. The hypotheses are written out in words (as you would in a psychological research report) and not just mathematical symbols.

Psychology Statistics For Dummies - Booktopia Psychology Statistics For Dummies - Booktopia

Some of the graphs appear to be formatted as would be a SPSS printout so it seems like presenting them as a computer output would be reasonable. The standard deviation (often abbreviated to Std. Dev. or SD) is the average deviation of scores in your data set from their mean score for a particular variable. The mean score is the average of scores on a variable. The standard deviation indicates the extent to which the scores on a variable deviate from the mean score. When working with psychology statistics you can classify variables according to their measurement properties. When you record variables on a data sheet, you usually record the values on the variables as numbers, because this makes statistical analysis easier. However, the numbers can have different measurement properties and these determine what types of analyses you can do with these numbers. The variable’s level of measurement is a classification system that tells you what measurement properties the values of a variable have.Reviewed by Chrislyn Randell, Professor, Metropolitan State University of Denver on 12/3/20, updated 2/26/21 This book is organized into Units, which are broken down into chapters. The unit and chapter organization makes sense for coverage of the material. In my introductory statistics course we do not cover linear regression, so I cover correlation earlier in my class. Since correlation is grouped into the Unit 3 (Additional Hypothesis Tests) it makes it a little more difficult to move out of this section and integrate elsewhere, but it is not a major concern for me. Equal intervals: This means that a unit difference on the measurement scale is the same regardless of where that unit difference occurs on the scale. Statistics changes little over time, so this book can be a standard for years to come. If APA format needs to be adjusted or examples (in the text and end-of-chapter problems) need to be updated, that can be easily done.

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