 +612 9045 4394  CHECKOUT # Core Statistical Concepts With Excel®

### An Interactive Modular Approach

eBook Published: 5th December 2018
ISBN: 9781544309057
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Core Statistical Concepts with Excel® connects statistical concepts to applications with Excel® using practical research examples. The text jointly promotes an understanding of Excel® and a deeper knowledge of core concepts through practice. Authors Gregory J. Privitera and Darryl Mayeaux provide students step-by-step instruction for using Excel® software as a useful tool not only to manage but also analyze data—all through the use of key themes, features, and pedagogy: an emphasis on student learning, a focus on current research, and integration of Excel® to introduce statistical concepts.

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

ISBN: 9781544309057
ISBN-10: 1544309058
Audience: Tertiary; University or College
Format: ePUB
Language: English
Number Of Pages: 376
Published: 5th December 2018
Publisher: SAGE Publications
Edition Number: 1

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