Statistics II for Dummies Learn to: * Increase your skills in data
analysis * Sort through and test models * Make predictions * Apply
statistics to real-world situations Deborah Rumsey, PhD Author of
Statistics For Dummies and Statistics Workbook For Dummies The fun
and easy way(r) to enhance your grasp of statistics Need to expand
your statistics knowledge and move on to Statistics II? This
friendly, hands-on guide gives you the skills you need to take on
multiple regression, analysis of variance (ANOVA), Chi-square
tests, nonparametric procedures, and other key topics. Statistics
II For Dummies also provides plenty of test-taking strategies as
well as real-world applications that make data analysis a snap,
whether you're in the classroom or at work. * Begin with the
basics - review the highlights of Stats I and expand on simple
linear regression, confidence intervals, and hypothesis tests *
Start making predictions - master multiple, nonlinear, and logistic
regression; check conditions; and interpret results * Analyze
variance with ANOVA - break down the ANOVA table, one-way and
two-way ANOVA, the F-test, and multiple comparisons * Connect with
Chi-square tests - examine two-way tables and test categorical data
for independence and goodness-of-fit * Leap ahead with
nonparametrics - grasp techniques used when you can't assume
your data has a normal distribution Open the book and find: *
Up-to-date methods for analyzing data * Full explanations of
Statistics II concepts * Clear and concise step-by-step procedures
* Dissection of computer output * Lots of tips, strategies, and
warnings * Ten common errors in statistical conclusions * Everyday
statistics applications * Tables for completing calculations used
in the book
The ideal supplement and study guide for students preparing for
advanced statistics
Packed with fresh and practical examples appropriate for a range of
degree-seeking students, Statistics II For Dummies helps any reader
succeed in an upper-level statistics course. It picks up with data
analysis where Statistics For Dummies left off, featuring new and
updated examples, real-world applications, and test-taking
strategies for success. This easy-to-understand guide covers such
key topics as sorting and testing models, using regression to make
predictions, performing variance analysis (ANOVA), drawing test
conclusions with chi-squares, and making comparisons with the Rank
Sum Test.
Deborah Rumsey, PhD, is a Statistics Education Specialist and
Auxiliary Faculty Member in the Department of Statistics at The
Ohio State University. She is the author of Statistics For Dummies
(978-0-7645-5423-0), Statistics Workbook For Dummies
(978-0-7645-8466-4), and Probability For Dummies
(978-0-471-75141-0).
Deborah Rumsey, PhD (Westerville, OH) is Director of the Ohio State University Mathematics and Statistics Learning Center, Director of the Consortium of the Advancement of Undergraduate Statistics Education (CAUSE), and a member of the Executive Committee of the American Statistical Association Section on Statistics Education.
Inhaltsangabe
Introduction. Part I: Tackling Data Analysis and Model-Building Basics. Chapter 1: Beyond Number Crunching: The Art and Science of Data Analysis. Chapter 2: Finding the Right Analysis for the Job. Chapter 3: Reviewing Confi dence Intervals and Hypothesis Tests. Part II: Using Different Types of Regression to Make Predictions. Chapter 4: Getting in Line with Simple Linear Regression. Chapter 5: Multiple Regression with Two X Variables. Chapter 6: How Can I Miss You If You Won't Leave? Regression Model Selection. Chapter 7: Getting Ahead of the Learning Curve with Nonlinear Regressio. Chapter 8: Yes, No, Maybe So: Making Predictions by Using Logistic Regression. Part III: Analyzing Variance with ANOVA. Chapter 9: Testing Lots of Means? Come On Over to ANOVA! Chapter 10: Sorting Out the Means with Multiple Comparisons. Chapter 11: Finding Your Way through Two-Way ANOVA. Chapter 12: Regression and ANOVA: Surprise Relatives! Part IV: Building Strong Connections with Chi-Square Tests. Chapter 13: Forming Associations with Two-Way Tables. Chapter 14: Being Independent Enough for the Chi-Square Test. Chapter 15: Using Chi-Square Tests for Goodness-of-Fit (Your Data, Not Your Jeans). Part V: Nonparametric Statistics: Rebels without a Distribution. Chapter 16: Going Nonparametric. Chapter 17: All Signs Point to the Sign Test and Signed Rank Test. Chapter 18: Pulling Rank with the Rank Sum Test. Chapter 19: Do the Kruskal-Wallis and Rank the Sums with the Wilcoxon. Chapter 20: Pointing Out Correlations with Spearman's Rank. Part VI: The Part of Tens. Chapter 21: Ten Common Errors in Statistical Conclusions. Chapter 22: Ten Ways to Get Ahead by Knowing Statistics. Chapter 23: Ten Cool Jobs That Use Statistics. Appendix: Reference Tables. Index.
