The statistics speak for themselves: enrollment in college statistics courses is up 45 percent over the last decade, the number of college-bound students taking the AP Statistics Exam nearly doubled from 2000 to 2003, and Statistics For Dummies has sold more than 65,000 copies in just over two years! This new guide takes statistics students to the next level, offering a refresher on statistics basics and covering concepts and topics typically encountered in second-semester statistics courses, including boxplots and scatterplots, Chebyshev's inequality, outliers, Z-scores, hypothesis tests, and Simpson's paradox.
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Deborah Rumsey has a PhD in Statistics from The Ohio State University (1993). She is a Statistics Education Specialist/Auxiliary Faculty Member for the Department of Statistics. Dr. Rumsey has been given the distinction of being named a Fellow of the American Statistical Association. She has also won the Presidential Teaching Award from Kansas State University. She is the author of Statistics For Dummies, Statistics Workbook For Dummies, and Probability For Dummies. She has published numerous papers and given many professional presentations on the subject of statistics education. Her passions include being with her family, bird watching, solving Sudoku puzzles, getting more seat time on her Kubota tractor, and cheering the Ohio State Buckeyes on to another National Championship.
Packed with examples, steps for problem-solving, and computer output The fun and easy way to analyze data, build models, and get ahead in your class Take your statistics skills to the next level! This easy-to-follow guide walks you through second-semester topics, explaining everything from t-tests and regression to ANOVA, sign tests, and fitting curves to your data. You'll see how to identify and work through problems, avoid common errors, understand the jargon -- and even improve your grade with savvy strategies. Discover how to * Review and extend intro stat methods * Make predictions with multiple regression * Compare many means by using ANOVA * Use Chi-square to test for independence * Understand and use nonparametric statistics
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