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# Data Sense: An Introduction to Statistics for the Behavioral Sciences

**Author(s):** * Barton Poulson *

** Edition: ** 1

** Copyright: ** 2014

** Pages: ** 142

** Data Sense: An Introduction to Statistics for the Behavioral Sciences** is fundamentally about data analysis. It uses common methods of gathering and analyzing data which allows students to construct stories about people. This text is accompanied by a set of over seventy professionally produced lecture videos. These videos are designed to explain and illustrate the concepts and techniques in this book in the most effective and concise way possible. In addition, the videos are optimized for viewing on mobile devices, so you can take your learning with you anywhere.

**Chapter 1 Introduction**

Data Analysis as Storytelling

Giving Support to Stories with Data

Theory in Data Analysis and Storytelling

Why Storytelling and Theory Matter

All Stories are Ultimately Wrong

Purposes of Analysis

Some Terminology

Univariate Descriptions

Association (i.e., Bivariate/Multivariate Descriptions)

Causality

Warning: Cause-and-Effect Is Harder Than You Think

Levels of Measurement

Categorical Variables

Quantitative Variables**Chapter 2 Distributions**

Introduction to Distributions

New Terms

Frequency Distribution Tables

Bar Charts

Pie Charts

Problems with Pie Charts

Boxplots

Tools for Making Boxplots

Histograms

Shape

Modes

Skewness

Kurtosis**Chapter 3 Central Tendency**

Introduction

Distributions with Different Centers

Contents

The Mode

Calculating the Mode

Example of the Mode with a Well-Behaved Data Set

Example of the Mode with an Outlier

Example of the Mode with Open-Ended or Undefined Scores

The Median

Example of the Median with a Well-Behaved Data Set

Example of the Median with an Outlier

Example of the Median with Open-Ended or Undefined Scores

The Mean

Calculating the Mean for a Population

Calculating the Mean for a Sample

Example of the Mean with a Well-Behaved Data Set

Example of the Mean with an Outlier

Example of the Mean with Open-Ended or Undefined Scores

Relationship of the Measures in Skewed Distributions**Chapter 4 Variability**

Introduction

Distributions with Different Variability

Effects of Variability

The Range

Example of the Range with a Well-Behaved Data Set

Example of the Range with an Outlier

Example of the Range with Open-Ended or Undefined Scores

Evaluating the Range

Quartiles: The “Five-Number Summary” and the Interquartile Range (IQR)

Example of the IQR with a Well-Behaved Data Set

Example of the IQR with an Outlier

Example of the IQR with Open-Ended or Undefined Scores

Evaluating the IQR

Degrees of Freedom (df)

The Standard Deviation and Variance

Calculating the Population Variance

Calculating the Population Standard Deviation

Calculating the Sample Variance

Calculating the Sample Standard Deviation

Example of the Standard Deviation with a Well-Behaved Data Set

Example of the Standard Deviation with an Outlier

Example of the Standard Deviation with Open-Ended or Undefined Scores

Evaluating the Variance and Standard Deviation

Online Calculator for Variance and SD**Chapter 5 z-Scores**

Introduction

Calculating z-Scores

Calculating z-Scores from a Population

Calculating z-Scores from a Sample

Comparing Two z-Scores

Computing X Scores from z-Scores

z-Distributions

The Standard Normal Distribution

Areas under the Standard Normal Distribution**Chapter 6 Sampling Distributions**

Introduction

Bias in Estimation

The Central Limit Theorem

Z-Scores for Sample Means**Chapter 7 Estimation**

Representative Samples

The Purpose of Estimation

Accuracy and Precision

Point Estimates

Confidence Intervals

Calculating Confidence Intervals

Values of z for Confidence Intervals

Worked Solution #1

Worked Solution #2

Worked Solution #3

Influences on Confidence Intervals**Chapter 8 Hypothesis Testing**

Introduction

Effect Sizes

Cohen’s d

Calculating Cohen’s d

Interpreting Cohen’s d

Other Measures of Effect Sizes

p-Values

p-Values and Sample Size

Introduction to Hypothesis Testing

The Logic of Hypothesis Testing

Hypotheses

The Null Hypothesis and the Alternative Hypothesis

Directional (one-tailed) Hypotheses

Nondirectional (two-tailed) Hypotheses

Retaining or Rejecting the Null Hypothesis

Type I and Type II Errors

Type I Errors

Type II Errors

The Meaning of Statistical Significance

The One Sample z-Test

Calculating the One Sample z-Test

Effect Size for the One Sample z-Test**Chapter 9 t-Tests**

Introduction

The t-Distributions

The One-Sample t-Test

Calculating the One-Sample t-Test

Effect Size for the One-Sample t-Test

The Repeated Measures t-Test

Calculating the Repeated Measures t-Test

Effect Size for the Repeated Measures t-Test

The Two-Sample t-Test

Calculating the Two-Sample t-Test

Effect Size for the Two-Sample t-Test**Chapter 10 The Analysis of Variance**

Introduction

Comparing Means

Analyzing Variance

Hypotheses

Test Statistic and Distribution

Post-Hoc Tests

Effect Size

Two-Way ANOVA**Chapter 11 Correlation and Regression**

Introduction

The Correlation Coefficient

Regression

Regression Coefficients and Predicted Values

Calculating Regression Coefficients

Outliers in Regression

Effect Size: R2

Hypothesis Tests

Hypotheses for Correlations

Hypotheses for Regression**Chapter 12 Chi-Squared**

Introduction

Expected Frequencies

The Chi-Squared Distributions

The Goodness-of-Fit Test

Hypotheses for the Goodness-of-Fit Test

Expected Frequencies for the Goodness-of-Fit Test

Degrees of Freedom for the Goodness-of-Fit Test

The Test for Independence

Hypotheses for the Test for Independence

Expected Frequencies for the Test for Independence

Degrees of Freedom for the Test for Independence

Hypothesis Tests

Effect Size**Conclusion**

**Barton Poulson**

Barton Poulson is the founder of the data analysis training site, datalab.cc. He has a PhD in social and personality psychology and has taught data analysis, research methods, and data visualization at Hunter College, Lehman College, Brigham Young University, the University of Utah, and Utah Valley University, and online for lynda.com. Bart lives with his wife and three children in Salt Lake City, Utah. You can learn more about his projects and interests at www.bartonpoulson.com.

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