## Description

**Test Bank For Statistics for People Who (Think They) Hate Statistics Using R By J. Salkind**

**Test Bank For Statistics for People Who (Think They) Hate Statistics Using R By Neil J. Salkind, Leslie A. Shaw, ISBN: 9781544324579**

Neil J. Salkind’s bestselling *Statistics for People Who (Think They) Hate Statistics *has been helping ease student anxiety around an often intimidating subject since it first published in 2000. Now the bestselling SPSS® and Excel® versions are joined by a text for use with the R software, **Statistics for People Who (Think They) Hate Statistics Using R**. New co-author Leslie A. Shaw carries forward Salkind’s signature humorous, personable, and informative approach as the text guides students in a grounding of statistical basics and R computing, and the application of statistics to research studies. The book covers various basic and advanced statistical procedures, from correlation and graph creation to analysis of variance, regression, non-parametric tests, and more.

**Table Of Content**

What You Will Learn in This Chapter

Why Statistics?

A 5-Minute History of Statistics

Statistics: What It Is (and Isn’t)

What Am I Doing in a Statistics Class?

Ten Ways to Use This Book (and Learn Statistics at the Same Time!)

What Else Does This Book Contain?

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

A Very Short History of R

The Pluses of Using R

The Minuses of Using R

Other Reasons to Use R?

A Short Note to You (and to Your Instructor) About Open Source (Again!)

Where to Find and Download R

Packages and Functions in R

A Note About Formatting

Bunches of Data—Free!

Getting R Help

Getting Help on Help

Some Important Lingo

Where to Find RStudio and How to Install It

Take RStudio for a Test Ride

Ordering From RStudio

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

The Grand Tour and All About Those Four Panes

RStudio Pane Goodies

Showing Your Stuff—Working With Menus and Tabs and a Sample Data Analysis Using RStudio

The Basics: +, –, ?, *, and More: Using Operators

Working With Data

Let’s See What’s in the Workspace

Reading in Established Data Sets

Oops! How Do You Correct Console Errors?

Pointing and Clicking to Open a Data Set

Computing Some Statistics

Ten Important Things to Remember About R and RStudio (but Not Necessarily in Order of Importance)

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Computing the Mean

Computing the Median

Computing the Mode

When to Use What Measure of Central Tendency (and All You Need to Know About Scales of Measurement for Now)

Using the Computer to Compute Descriptive Statistics

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Why Understanding Variability Is Important

Computing the Range

Computing the Standard Deviation

Step-by-Step

What’s the Big Deal?

Computing the Variance

Using R to Compute Measures of Variability

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Why Illustrate Data?

Ten Ways to a Great Graphic

First Things First: Creating a Frequency Distribution

The Plot Thickens: Creating a Histogram

The Next Step: A Frequency Polygon

Cumulating Frequencies

Other Cool Ways to Chart Data

Using the Computer (R, That Is) to Illustrate Data

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

What Are Correlations All About?

Computing a Simple Correlation Coefficient

Understanding What the Correlation Coefficient Means

A Determined Effort: Squaring the Correlation Coefficient

Computing the Correlation Coefficient by Entering Data

Computing the Correlation Coefficient by Importing a File

Other Cool Correlations

Parting Ways: A Bit About Partial Correlation

Using R to Compute Partial Correlations

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

An Introduction to Reliability and Validity

Reliability: Doing It Again Until You Get It Right

Different Types of Reliability

Computing Cronbach’s Alpha

Using R to Calculate Cronbach’s Alpha

Understanding the R Output

Computing Interrater Reliability

How Big Is Big? Finally: Interpreting Reliability Coefficients

Validity: Whoa! What Is the Truth?

A Last Friendly Word

Validity and Reliability: Really Close Cousins

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

So You Want to Be a Scientist

Samples and Populations

The Null Hypothesis

The Research Hypothesis

What Makes a Good Hypothesis?

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Why Probability?

The Normal Curve (a.k.a. the Bell-Shaped Curve)

Our Favorite Standard Score: The z Score

Hypothesis Testing and z Scores: The First Step

Fat and Skinny Frequency Distributions

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

The Concept of Significance

Significance Versus Meaningfulness

An Introduction to Inferential Statistics

An Introduction to Tests of Significance

Be Even More Confident

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Introduction to the One-Sample z Test

The Path to Wisdom and Knowledge

Computing the z Test Statistic

Using R to Perform a z Test

Special Effects: Are Those Differences for Real?

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Introduction to the t Test for Independent Samples

The Path to Wisdom and Knowledge

Computing the t Test Statistic

The Effect Size and t(ea) for Two

Using R to Perform a t Test

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Introduction to the t Test for Dependent Samples

The Path to Wisdom and Knowledge

Computing the t Test Statistic

Using R to Perform a t Test

The Effect Size for t(ea) for Two (Again)

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Introduction to Analysis of Variance

The Path to Wisdom and Knowledge

Different Flavors of ANOVA

Computing the F Test Statistic

Using R to Compute the F Ratio

The Effect Size for One-Way ANOVA

But Where Is the Difference?

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Introduction to Factorial Analysis of Variance

The Path to Wisdom and Knowledge

A New Flavor of ANOVA

All of Those Effects

The Main Event: Main Effects in Factorial ANOVA

The Other Rows

Plotting the Means by Group

Even More Interesting Interaction Effects

Assumptions About Variances

Using R to Compute the F Ratio

Computing the Effect Size for Factorial ANOVA

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Introduction to Testing the Correlation Coefficient

The Path to Wisdom and Knowledge

Computing the Test Statistic

Causes and Associations (Again!)

Using R to Compute a Correlation Coefficient (Again)

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Introduction to Linear Regression

What Is Prediction All About?

The Logic of Prediction

Drawing the World’s Best Line (for Your Data)

How Good Is Your Prediction?

Using R to Compute the Regression Line

Understanding the R Output

The More Predictors the Better? Maybe

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Introduction to Nonparametric Statistics

Introduction to the Goodness-of-Fit (One-Sample) Chi-Square

Computing the Goodness-of-Fit Chi-Square Test Statistic

Introduction to the Test of Independence Chi-Square

Computing the Test of Independence Chi-Square Test Statistic

Using R to Perform Chi-Square Tests

Understanding the R Output

Other Nonparametric Tests You Should Know About

Real-World Stats

Summary

Time to Practice

Student Study Site

What You Will Learn in This Chapter

Multivariate Analysis of Variance

Repeated-Measures Analysis of Variance

Analysis of Covariance

Multiple Regression

Multilevel Models

Meta-Analysis

Logistic Regression

Factor Analysis

Path Analysis

Structural Equation Modeling

Summary

Student Study Site