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Core Statistical Concepts With Excel®
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Core Statistical Concepts With Excel®
An Interactive Modular Approach

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January 2019 | 376 pages | SAGE Publications, Inc

Proficiency with using Excel® is a key skill set students need when going on to graduate school in the behavioral sciences. Students struggle to understand core statistical concepts, and there is a need for resources that help make statistical concepts accessible in an appealing way.

 

Privitera and Mayeaux’s Revealing Core Statistical Concepts in Excel®: An Interactive Modular Approach is a flexible textbook for introductory students. The text jointly promotes an understanding of Excel® and a deeper knowledge of core concepts through practice. Each chapter begins with introductory vignettes designed to disarm student apprehension. These stories are paired with step-by-step exercises and recurring toolkit pedagogy to help students better understand core statistical concepts within Excel® through actual examples. 

 
Preface to the Instructor
 
To the Student
 
Orientation to Excel
 
About the Authors
 
SECTION I. CENTRAL TENDENCY AND VARIABILITY
 
Learning Unit 1. Mean, Median, and Mode
Excel Toolbox

 
Mean

 
Median

 
Mode

 
Choosing an Appropriate Measure of Central Tendency

 
 
Learning Unit 2. Variability
Excel Toolbox

 
Range

 
Quartiles and Interquartiles

 
Variance

 
Standard Deviation

 
 
Learning Unit 3. Shapes of Distributions
Excel Toolbox

 
Normal Distribution Created With Frequency Array Function

 
Normal Distribution Created With a PivotTable

 
Creating a Graph of a Frequency Distribution

 
Skewed Distribution Created With a PivotTable

 
 
SECTION II. PROBABILITY
 
Learning Unit 4. Probability and the Normal Distribution
Excel Toolbox

 
Calculating Probability

 
Expected Value and the Binomial Distribution

 
Relative Frequency and Probability

 
Normal Distribution

 
 
Learning Unit 5. The Standard Normal Distribution: z Scores
Excel Toolbox

 
The Standard Normal Distribution

 
The Unit Normal Table: A Brief Introduction

 
 
Learning Unit 6. Sampling Distributions
Excel Toolbox

 
Selecting Samples From Populations

 
Sampling Distributions: The Mean

 
Computing Characteristics of the Sample Mean Using Excel

 
Sampling Distributions: The Variance

 
Computing Characteristics of the Sample Variance Using Excel

 
 
SECTION III. EVALUATING THE NATURE OF EFFECTS
 
Learning Unit 7. Hypothesis Testing: Significance, Effect Size, and Confidence Intervals
Inferential Statistics and Hypothesis Testing

 
Four Steps to Hypothesis Testing

 
Making a Decision: Types of Error

 
Nondirectional and Directional Alternatives to the Null Hypothesis

 
Effect Size

 
Estimation and Confidence Intervals

 
Delineating Statistical Effects for Hypothesis Testing

 
 
Learning Unit 8. Power
Detecting “Effects”

 
Effect Size, Power, and Sample Size

 
 
SECTION IV. COMPARING MEANS: SIGNIFICANCE TESTING, EFFECT SIZE, AND CONFIDENCE INTERVALS
 
Learning Unit 9. t Tests: One-Sample, Two-Independent-Sample, and Related-Samples Designs
Excel Toolbox

 
Origins of the t Tests

 
Computing the One-Sample t Test

 
Computing the Two-Independent-Sample t Test

 
Computing the Related-Samples t Test

 
 
Learning Unit 10. One-Way Analysis of Variance: Between-Subjects and Repeated-Measures Designs
Excel Toolbox

 
An Introduction to Analysis of Variance (ANOVA)

 
One-Way Between-Subjects ANOVA

 
One-Way Within-Subjects ANOVA

 
Post Hoc Test Using Tukey’s HSD

 
 
Learning Unit 11. Two-Way Analysis of Variance: Between-Subjects Factorial Design
Excel Toolbox

 
An Introduction to Factorial Design

 
Describing Variability: Main Effects and Interactions

 
Computing the Two-Way Between-Subjects ANOVA

 
Analyzing Main Effects and Interactions

 
Measuring Effect Size With Eta Squared

 
Computing the Two-Way Between-Subjects ANOVA Using the Analysis ToolPak

 
 
SECTION V. IDENTIFYING PATTERNS AND MAKING PREDICTIONS
 
Learning Unit 12. Correlation
Excel Toolbox

 
The Structure of Data Used for Identifying Patterns

 
Fundamentals of the Correlation

 
The Strength of a Correlation

 
The Pearson Correlation Coefficient

 
Effect Size: The Coefficient of Determination

 
Hypothesis Testing: Testing for Significance

 
Limitations in Interpretation: Causality, Outliers, and Restriction of Range

 
An Alternative to Pearson for Ranked Data: Spearman

 
An Overview of Other Alternatives to Pearson

 
 
Learning Unit 13. Linear Regression
Excel Toolbox

 
Fundamentals of Linear Regression

 
Using the Method of Least Squares to Find the Regression Line

 
Using Regression to Determine Significance

 
Computing the Analysis of Regression With the Analysis ToolPak

 
 
Appendix A: Core Statistical Concepts
A1: Normal and Skewed Distributions

 
A2: Scales of Measurement

 
A3: Outliers

 
A4: The Empirical Rule for Normal Distributions

 
A5: Chebyshev’s Theorem for Any Type of Distribution

 
A6: Expected Value as a Long-Term Mean

 
A7: The Informativeness of the Mean and Standard Deviation for Finding Probabilities

 
A8: Comparing Differences Between Two Groups

 
A9: Calculation and Interpretation of the Pooled Sample Variance

 
A10: Reducing Standard Error by Computing Difference Scores

 
A11: Categories of Related-Samples Designs

 
A12: Degrees of Freedom for Parametric Tests

 
 
Appendix B: Global Excel Skills
B1: Viewing in Cells the Functions or Formulas Versus the Results of Those Functions or Formulas

 
B2: Formatting Cells: Decimals, Alignment, Merge Cells, Fonts, Bold, Borders, Superscripts, Subscripts

 
B3: Freezing the Display of Some Rows and Columns

 
B4: Highlighting Portions of Spreadsheet, Pasting, or Filling

 
B5: Sorting Data in a Spreadsheet

 
B6: Anchoring Cell References

 
B7: Inserting (Creating) and Formatting a Chart (Graph of Data)

 
B8: Inserting Equations

 
 
Appendix C: Statistical Tables
C1: The Unit Normal Table

 
C2: Critical Values for the t Distribution

 
C3: Critical Values for the F Distribution

 
C4: The Studentized Range Statistic (q)

 
C5: Critical Values for the Pearson Correlation

 
C6: Critical Values for the Spearman Correlation

 
 
Glossary
 
References
 
Index

Supplements

Instructor Resource Site

study.sagepub.com/priviteraexcel1e

A Test Bank is available with this text on a password-protected Instructor Resource Site.


may adopt in future. got exam copy too late for course. Looks solid, and covers a lot of professional uses of excel.

Mr Gwen Urey
Urban/Regional Planning Dept, Cal State Polytechnic-Pomona
September 10, 2018

Sample Materials & Chapters

Learning Unit 7: Hypothesis Testing

Learning Unit 9: t Tests


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Gregory J. Privitera

Gregory J. Privitera is an associate professor of psychology at St. Bonaventure University. Dr. Privitera received his PhD in behavioral neuroscience in the field of psychology at the State University of New York at Buffalo. He went on to complete postdoctoral research at Arizona State University before beginning his tenure at St. Bonaventure University. He is an author of multiple books on statistics, research methods, and the psychology of eating, in addition to authoring over two-dozen peer-reviewed scientific articles aimed at advancing our understanding of health and promoting the intake of healthier diets for children and adults. He... More About Author

Darryl James Mayeaux

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ISBN: 9781544309040
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