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Product Description
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.
From the Back Cover
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
Learn to:
- Increase your skills in data analysis
- Sort through and test models
- Make predictions
Apply statistics to real–world situations
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