Student Friendly Statistics

Note: Supplemental materials are not guaranteed with Rental or Used book purchases.

ISBN: 9780130265210 | 0130265217
Cover: Paperback
Copyright: 9/21/2000

Sorry, this item is currently not available.

This accessible introduction presents statistics in a simple, yet meaningful manner using concrete examples of what researchers do with statistics. Employing an interactive, active-learning presentation, this text effectively teaches advanced statistics with a straightforward approach that helps readers who are not strong in mathematics understand the concepts.Text addresses statistical concepts including influences on behavior, populations, sample means, addressing researcher's questions, n dimensions, variables and analyzing categorical data, as well as providing techniques for coping with math and test anxiety.For non-mathematically focused individuals looking to understand basic and advanced statistical concepts.

The Researcher's Question

(8)

The Researcher's Question

(1)

Example 1: Isen, Clark, and Schwartz (1976)

(1)

Example 2: A Lasting Friendship

(1)

Other Examples of Statistics

(1)

International Banking

(1)

What Makes a Person Hardy?

(1)

A Bit about Tools: Scales of Measurement

(2)

The Trail Ahead

(1)

Review

(1)

Exercises

(1)

Answers

(1)

Thinking about Influences on Behavior

(10)

Scores and Influences

(1)

Categorizing Influences

(1)

Example of a Nuisance Variable

(1)

Examples of Confounds

(1)

Between-Group versus Within-Group Influences

(1)

N Effects and Error

(2)

The Trail Ahead

(1)

Review

(1)

Exercises

(3)

Answers

(2)

Describing Influences on Behavior

(17)

The Mean as Central Tendency

(3)

Using Symbols

(1)

A Problem with the Mean

(1)

The Median

(1)

The Mode

(1)

Central Tendency and the N Effect

(1)

Central Tendency Isn't Everything

(1)

Looking at a Set of Scores: Frequency Distributions

(2)

Frequency Distributions Have Shapes

(1)

Measuring the Spread of the Distribution

(3)

Total Size of the Distribution: The Range

(1)

A Better Measure: Variability about the Mean

(1)

Standard Deviation (SD)

(1)

Remember the Meaning: Average Deviation

(1)

Variability and Error

(1)

Viewing Data from an Experiment

(1)

Reference

(1)

Review

(1)

Exercises

(2)

Answers

(2)

Looking at Populations

(7)

Samples and Populations

(1)

Normal Distributions and Standard Normal Distributions

(1)

Recycling Distributions

(2)

An Example

(2)

Using Distributions

(1)

Cumulative Distributions

(1)

Being Precise: A More Exact Normal Distribution

(1)

Review

(1)

Exercises

(1)

Answers

(1)

How Accurate Are Sample Means?

(8)

Two Determinants of Accuracy of Sample Means

(2)

An Example

(1)

Looking at a Distribution of Sample Means

(2)

Summarize What You Have Learned

(1)

Putting the Pieces in Perspective

(1)

Review

(1)

Exercises

(2)

Answers

(1)

Answering the Researcher's Question by Turning It Upside Down

(18)

The Null Hypothesis

(1)

An Experiment with Nothingness

(1)

Expanding the Null Hypothesis: The Sampling Distribution of the Difference Between Means

(3)

Using the SDODBM

(1)

A Borderline Between the Likely and Unlikely Regions

(1)

Let's Talk About Our Decision

(1)

Probability Statements

(1)

Practice

(1)

Calculating the SEdiff

(1)

Perspective

(1)

Another View: The Big Decision

(3)

Type I Errors

(1)

Type II Errors

(2)

A 2 x 2 Decision Box

(1)

Power: Avoiding Type II Errors

(1)

Review

(1)

Exercises

(2)

Answers

(1)

A Recipe for Answering the Researcher's Question

(23)

The Big Picture

(2)

Calculating t Values

(2)

Step-By-Step Method for Calculating t

(1)

Expanding the Idea of t

(5)

tobtained and tcritical

(1)

t with Different Sample Sizes

(5)

Measure of Total Sample Size: Degrees of Freedom

Finding tcritical in a t-Table

(1)

Putting the Idea to Use

(1)

Conducting the t-test: Summary

(1)

One-Tailed Tests

(2)

Using the One-Tailed Test

(1)

Variation in the Value of p

(1)

Reporting t-Tests in Articles

(1)

What Happens with a Borderline p-Value?

(1)

The Meaning of Statistical Decisions

(1)

``Significance'' Is a Lousy Term

(1)

A Big t Means Little

(1)

You Never Prove the Null Hypothesis

(1)

Relations Relevant to Statistical Decisions

(2)

Effect Size

(1)

Power

(1)

Putting This Together: t-Values and Research Design

(2)

Effects of Confounds

(1)

Some More Details

(2)

Standard Error of the Difference, Part 2: Unequal Sample Size

(1)

You've Learned about One Type of t-Test: t-Test for Independent Samples

(1)

t-Test for Dependent Samples

(1)

Review

(1)

Exercises

(3)

Answers

(2)

Expanding Our Thinking to n Dimensions: Analysis of Variance

(23)

Gosset and Fisher

(2)

Influences of a Score, Part 1: Reminder from the t-Test

(1)

Influences of a Score, Part 2

(5)

The Model

(1)

Rearranging the Deviations

(1)

Sums of Squared Deviations

(1)

Deviation Tables

(1)

Influences as Sources of Variance

100

(3)

Source Tables

101

(2)

Checking Your Calculations

103

(1)

Summary: Calculate ANOVA in Two Easy Tables

103

(1)

Meaning of F

103

(1)

F Distributions

104

(2)

Degrees of Freedom and the F Table

104

(2)

Reporting F-Tests in Articles

106

(1)

F's and t's

106

(2)

Effects Size and Power

108

(1)

Effects of Confounds

108

(1)

Within-Participant Designs

108

(1)

Final Summary: Calculating ANOVA

108

(1)

How to Calculate F for a Between-Participant Design

108

(1)

Review

109

(1)

Exercises

110

(2)

Answers

112

(3)

Using More Than Two Groups

115

(12)

The Example Experiment

115

(1)

Doing the Multilevel Analysis of Variance

116

(3)

Completed Tables

118

(1)

Interpretation F in the Multilevel Case

119

(1)

Follow-Up Tests

119

(2)

A Priori Hypotheses: Planned Comparisons

119

(1)

After the Experiment: Post-Hoc Tests Given a Significant F

120

(1)

The Pitfalls of Data Fishing

120

(1)

A Post-Hoc Test: The Scheffe Test

121

(1)

Computational Summary: Multilevel ANOVA for Between-Participant Designs

121

(1)

Review

122

(1)

Exercises

122

(2)

Answers

124

(3)

Using More Than One Independent Variable

127

(21)

An Example Study

128

(2)

Most Basic Levels: Cells

128

(1)

There Are Four Cell Means

129

(1)

The Entire Design

129

(1)

Next Level: Main Effects and Four Main Effect Means

129

(1)

Highest Level: One Grand Mean

129

(1)

The Example Made Concrete with Numbers

130

(1)

Interpreting the Main Effects

130

(1)

The Completed Table

131

(1)

Three N Effects in the 2 x 2 Factorial

132

(2)

Main Effect of IV A

132

(1)

Main Effect of IV B

132

(1)

Interaction of A and B

132

(2)

Where We Are Going

134

(1)

Five Sums of Squares in the Factorial Design

134

(3)

Error Deviations

134

(1)

Total

134

(1)

IV A Effect

134

(2)

IV B Effect

136

(1)

Interaction of A x B

136

(1)

Putting It Together: The Entire Deviation Formula

137

(1)

Time Out for a Review

138

(1)

Doing the ANOVA

138

(2)

The Sums of Squares

138

(1)

Source Table for a 2 x 2 Factorial Design

139

(1)

Compare the Obtained and Critical F's

139

(1)

Degrees of Freedom

140

(1)

Interpreting 2 x 2 Graphs

140

(2)

Review

142

(1)

Exercises

142

(2)

Answers

144

(4)

Relations Between Variables: Linear Regression and Correlation

148

(28)

Illustrating Relations between Variables: Graphs of Means

148

(1)

Illustrating Relations for all Scores: The Scatterplot

149

(1)

Regression Example

150

(2)

Correlation: The Strength of a Relation

152

(1)

Regression Lines

153

(2)

Slope: The Regression Coefficient

154

(1)

Intercept

154

(1)

Error

154

(1)

Using Regression for Prediction

155

(1)

Regression Equation

156

(1)

Summary Example

157

(1)

Letting the Computer ``Fit'' Your Regression Line

158

(1)

Measuring the Strength of a Relation: Correlation

158

(1)

z Scores and Correlation

159

(1)

z Score Correlation Formula

160

(2)

Correlation, Regression, and Variance: The Coefficient of Determination

162

(1)

Testing the Significance of Regression and Correlation Values

163

(1)

Two Limitations of Linear Regression and Correlation

164

(1)

Only Linear Relations are Measured

164

(1)

A Relation Does Not Imply Causality

165

(1)

The Third Variable Problem

165

(1)

Regression and Correlation versus t-Tests and ANOVA

166

(1)

Advanced Methods of Correlation and Regression

167

(2)

Correlation Matrices

167

(1)

Multiple Regression

168

(1)

Reference: Calculating Regression and Correlation Values

169

(1)

Step-by-Step Method for Regression and Correlation Values

170

(1)

Completed Step-by-Step Methods for Calculating Correlation

171

(1)

Review

171

(1)

Exercises

172

(3)

Answers

175

(1)

Analyzing Categorical Data

176

(11)

The Basic Idea of Chi-Square (χ2)

176

(2)

Testing the Significance of a Chi-Square Value

178

(1)

Expected Frequencies with More than Two Categories

179

(1)

Extending the Basic Idea to Contingencies

179

(2)

Contingency Tables

180

(1)

This is Chi-Square

181

(1)

Review

182

(1)

Exercises

182

(3)

Answers

185

(2)

Perspective: Looking Back at Your Journey

187

(6)

Descriptive Statistics

187

(1)

t-Test: Are These Two Samples the Same or Different?

188

(1)

ANOVA: One-Factor and Multifactor

188

(1)

Regression and. Correlation: Relations Between Variables

189

(1)

Relations between Statistics

189

(1)

Chi-Square for Categories

190

(1)

Have We Missed Something?

190

(1)

The Creative Nature of Statistics

190

(1)

Exercises

191

(1)

Answers

191

(2)

Appendix Coping with Math and Test Anxiety

193

(2)

Index

195

Please wait while the item is added to your bag...

FREE SHIPPING

Amazon no longer offers textbook rentals. We do!

Student Friendly Statistics

Summary

Table of Contents

Supplemental Materials