Introduction: You Do Not Need to Be a Statistician to Understand Statistics! |
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1 | (6) |
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Many Students Do Not Know What They're Getting Into |
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2 | (1) |
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Step 1 Identify the Problem |
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Step 2 State a Hypothesis |
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4 | (1) |
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Step 3 Identify the Independent Variable |
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4 | (1) |
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Step 4 Identify and Describe the Dependent Variable |
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5 | (1) |
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Step 5 Choose the Right Statistical Test |
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5 | (1) |
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Step 6 Use Data Analysis Software to Test the Hypothesis |
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5 | (1) |
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So, What's New in This Edition? |
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5 | (1) |
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6 | (1) |
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Do You Understand These Key Words and Phrases? |
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6 | (1) |
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Chapter 1 Identifying A Research Problem And Stating Hypotheses |
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7 | (26) |
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7 | (1) |
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Step 1 Identify the Problem |
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Characteristics of a Good Problem Statement |
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8 | (1) |
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Finding a Good Research Problem |
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8 | (1) |
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The Problem Is Interesting to the Researcher |
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9 | (1) |
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The Scope of the Problem Is Manageable by the Researcher |
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9 | (1) |
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The Researcher Has the Knowledge, Time, and Resources Needed to Investigate the Problem |
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10 | (1) |
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The Problem Can Be Researched through the Collection and Analysis of Numeric Data |
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11 | (1) |
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Investigating the Problem Has Theoretical or Practical Significance |
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11 | (1) |
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It Is Ethical to Investigate the Problem |
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12 | (1) |
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Writing the Problem Statement |
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13 | (1) |
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Problem Statements Must Be Clear and Concise |
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13 | (1) |
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The Problem Statement Must Include All Variables to Be Considered |
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14 | (1) |
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The Problem Statement Should Not Interject the Researcher's Bias |
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15 | (1) |
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Summary of Step 1 Identify the Problem |
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15 | (1) |
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Step 2 State a Hypothesis |
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16 | (13) |
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An Example of Stating Our Hypothesis |
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16 | (1) |
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17 | (1) |
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The Direction of Hypotheses |
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17 | (1) |
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Using Directional Hypotheses to Test a "Greater Than" Relationship |
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18 | (1) |
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Using Directional Hypotheses to Test a "Less Than" Relationship |
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18 | (1) |
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Nondirectional Hypotheses |
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19 | (1) |
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Hypotheses Must Be Testable via the Collection and Analysis of Data |
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20 | (1) |
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Research versus Null Hypotheses |
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20 | (1) |
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Stating Null Hypotheses for Directional Hypotheses |
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20 | (1) |
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Issues Underlying the Null Hypothesis for Directional Research Hypotheses |
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21 | (1) |
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Stating Null Hypotheses for Nondirectional Hypotheses |
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22 | (1) |
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A Preview of Testing the Null Hypothesis |
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23 | (3) |
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Where Does That Leave Us? |
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26 | (2) |
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Statistical Words of Wisdom |
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28 | (1) |
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Summary of Step 2 State a Hypothesis |
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28 | (1) |
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Do You Understand These Key Words and Phrases? |
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29 | (1) |
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29 | (1) |
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29 | (1) |
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30 | (1) |
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The Case of Distance Therapy |
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30 | (1) |
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The Case of the New Teacher |
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30 | (1) |
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The Case of Being Exactly Right |
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31 | (1) |
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The Case of "Does It Really Work?" |
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31 | (1) |
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31 | (1) |
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The Case of Learning to Speak |
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32 | (1) |
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The Case of Kids on Cruises |
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32 | (1) |
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Chapter 2 Identifying The Independent And Dependent Variables In A Hypothesis |
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33 | (27) |
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33 | (1) |
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Step 3 Identify the Independent Variable |
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33 | (4) |
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Nonmanipulated Independent Variables |
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34 | (1) |
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Another Way of Thinking about Nonmanipulated Independent Variables |
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35 | (1) |
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Manipulated or Experimental Independent Variables |
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35 | (1) |
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Levels of the Independent Variable |
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36 | (1) |
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Summary of Step 3 Identify the Independent Variable |
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37 | (1) |
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Step 4 Identify and Describe the Dependent Variable |
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37 | (20) |
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Identifying Your Dependent Variable |
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37 | (2) |
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What Type of Data Are We Collecting? |
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39 | (1) |
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40 | (2) |
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Data Types---What Is the Good News? |
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42 | (1) |
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Summary of the Dependent Variable and Data Types |
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43 | (1) |
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Measures of Central Tendency |
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43 | (2) |
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The Mean, Median, and Mode---Measures of Central Tendency |
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45 | (5) |
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50 | (1) |
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Using Statistical Software to Analyze Our Data |
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51 | (5) |
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Summary of the First Part of Step 4: Identify and Describe the Dependent Variable |
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56 | (1) |
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Do You Understand These Key Words and Phrases? |
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57 | (1) |
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Do You Understand These Formulas? |
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57 | (1) |
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57 | (3) |
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Chapter 3 Measures Of Dispersion And Measures Of Relative Standing |
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60 | (27) |
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60 | (1) |
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60 | (10) |
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61 | (2) |
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63 | (4) |
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67 | (3) |
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Measures of Relative Standing |
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70 | (13) |
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71 | (6) |
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Computing and Interpreting T-Scores |
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77 | (1) |
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78 | (1) |
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79 | (1) |
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Using SPSS for T-Scores and Stanines---Not So Fast! |
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80 | (3) |
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83 | (1) |
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Do You Understand These Key Words and Phrases? |
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84 | (1) |
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Do You Understand These Formulas? |
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84 | (1) |
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85 | (2) |
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Chapter 4 Graphically Describing The Dependent Variable |
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87 | (28) |
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87 | (1) |
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Graphical Descriptive Statistics |
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87 | (12) |
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Graphically Describing Nominal Data |
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88 | (1) |
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88 | (2) |
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90 | (2) |
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Graphically Describing Quantitative Data |
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92 | (1) |
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92 | (5) |
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97 | (1) |
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Don't Let a Picture Tell You the Wrong Story! |
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97 | (2) |
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Summary of Graphical Descriptive Statistics |
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99 | (1) |
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99 | (13) |
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Things That Can Affect the Shape of a Distribution of Quantitative Data |
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101 | (11) |
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Summary of the Normal Distribution |
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112 | (1) |
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Do You Understand These Key Words and Phrases? |
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113 | (1) |
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113 | (2) |
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Chapter 5 Choosing The Right Statistical Test |
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115 | (41) |
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115 | (1) |
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115 | (9) |
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The Central Limit Theorem |
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116 | (1) |
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The Sampling Distribution of the Means |
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117 | (7) |
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Summary of the Central Limit Theorem and the Sampling Distribution of the Means |
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124 | (1) |
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124 | (1) |
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Estimating Population Parameters Using Confidence Intervals |
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125 | (4) |
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125 | (2) |
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Type I and Type II Errors |
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127 | (2) |
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Predicting a Population Parameter Based on a Sample Statistic Using Confidence Intervals |
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129 | (8) |
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131 | (1) |
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Confidence Intervals for Alpha = .01 and Alpha = .10 |
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132 | (2) |
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Another Way to Think about z Scores in Confidence Intervals |
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134 | (1) |
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134 | (1) |
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Be Careful When Changing Your Alpha Values |
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135 | (1) |
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Do We Understand Everything We Need to Know about Confidence Intervals? |
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136 | (1) |
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Testing Hypotheses about a Population Parameter Based on a Sample Statistic |
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137 | (7) |
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Making a Decision about the Certification Examination Scores |
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138 | (3) |
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We Are Finally Going to Test Our Hypothesis! |
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141 | (1) |
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Testing a One-Tailed Hypothesis |
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141 | (3) |
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Testing a One-Tailed "Less Than" Hypothesis |
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144 | (1) |
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Summarizing What We Just Said |
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145 | (1) |
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Be Careful When Changing Your Alpha Values |
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146 | (1) |
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The Heart of Inferential Statistics |
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147 | (5) |
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148 | (1) |
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149 | (1) |
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Great News---We Will Always Use Software to Compute Our p Value |
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150 | (2) |
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Step 5 Choose the Right Statistical Test |
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152 | (2) |
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You Already Know a Few Things |
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152 | (1) |
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A Couple of Notes about the Table |
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153 | (1) |
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Summary of Step 5 Choose the Right Statistical Test |
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154 | (1) |
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Do You Understand These Key Words and Phrases? |
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154 | (1) |
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Do You Understand These Formulas and Symbols? |
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154 | (1) |
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155 | (1) |
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Chapter 6 The One-Sample F-Test |
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156 | (25) |
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156 | (1) |
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Welcome to the Guinness Breweries |
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156 | (1) |
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157 | (6) |
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157 | (2) |
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Determining the Critical Value of t |
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159 | (1) |
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159 | (2) |
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Be Careful Computing Degrees of Freedom |
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161 | (1) |
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Let's Get Back to Our Anxiety Hypothesis |
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162 | (1) |
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Plotting Our Critical Value of t |
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162 | (1) |
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The Statistical Effect Size of Our Example |
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162 | (1) |
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Let's Look at a Directional Hypothesis |
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163 | (3) |
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165 | (1) |
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165 | (1) |
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166 | (2) |
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Important Note about Software Packages |
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167 | (1) |
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Let's Use the Six-Step Model! |
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168 | (8) |
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The Case of Slow Response Time |
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168 | (3) |
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The Case of Stopping Sneezing |
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171 | (3) |
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The Case of Growing Tomatoes |
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174 | (2) |
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176 | (1) |
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Do You Understand These Key Words and Phrases? |
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177 | (1) |
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Do You Know These Formulas? |
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177 | (1) |
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177 | (4) |
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Chapter 7 The Independent-Sample T-Test |
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181 | (36) |
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181 | (1) |
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If We Have Samples from Two Independent Populations, How Do We Know If They Are Significantly Different from One Another? |
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182 | (15) |
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The Sampling Distribution of Mean Differences |
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182 | (3) |
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Calculating the t Value for the Independent-Sample t-Test |
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185 | (1) |
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185 | (5) |
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190 | (1) |
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191 | (1) |
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Note on Variance and the t-Test |
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192 | (1) |
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The Statistical Effect Size of Our Example |
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192 | (1) |
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Let's Try Another Example |
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193 | (2) |
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195 | (1) |
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How Does This Work for a Directional Hypothesis? |
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195 | (2) |
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Reminder---Always Pay Attention to the Direction of the Means! |
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197 | (1) |
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Putting the Independent-Sample t-Test to Work |
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197 | (12) |
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The Case of the Cavernous Lab |
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197 | (5) |
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The Case of the Report Cards |
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202 | (4) |
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The Case of the Anxious Athletes |
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206 | (3) |
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209 | (1) |
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Do You Understand These Key Words and Phrases? |
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210 | (1) |
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Do You Understand These Formulas? |
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210 | (1) |
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211 | (1) |
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The Case of the Homesick Blues |
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211 | (1) |
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The Case of the Cold Call |
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211 | (1) |
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The Case of the Prima Donnas |
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212 | (1) |
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The Case of the Wrong Side of the Road |
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213 | (1) |
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The Case of Workplace Satisfaction |
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214 | (1) |
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The Case of the Flower Show |
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215 | (2) |
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Chapter 8 The Dependent-Sample T-Test |
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217 | (27) |
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217 | (1) |
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That's Great, but How Do We Test Our Hypotheses? |
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217 | (1) |
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Independence versus Dependence |
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218 | (8) |
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Computing the t Value for a Dependent-Sample t-Test |
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218 | (1) |
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Testing a One-Tailed "Greater Than" Hypothesis |
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219 | (3) |
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The Effect Size for a Dependent-Sample t-Test |
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222 | (1) |
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Testing a One-Tailed "Less Than" Hypothesis |
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223 | (3) |
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Testing a Two-Tailed Hypothesis |
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226 | (3) |
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Let's Move Forward and Use Our Six-Step Model |
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229 | (3) |
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Step 1 Identify the Problem |
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229 | (1) |
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Step 2 State a Hypothesis |
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229 | (1) |
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Step 3 Identify the Independent Variable |
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230 | (1) |
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Step 4 Identify and Describe the Dependent Variable |
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230 | (1) |
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Step 5 Choose the Right Statistical Test |
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231 | (1) |
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Step 6 Use Data Analysis Software to Test the Hypothesis |
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231 | (1) |
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The Case of the Unexcused Students |
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232 | (2) |
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Step 1 Identify the Problem |
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232 | (1) |
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Step 2 State a Hypothesis |
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232 | (1) |
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Step 3 Identify the Independent Variable |
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233 | (1) |
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Step 4 Identify and Describe the Dependent Variable |
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233 | (1) |
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Step 5 Choose the Right Statistical Test |
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233 | (1) |
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Step 6 Use Data Analysis Software to Test the Hypothesis |
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233 | (1) |
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The Case of Never Saying Never |
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234 | (3) |
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Step 1 Identify the Problem |
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235 | (1) |
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Step 2 State a Hypothesis |
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235 | (1) |
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Step 3 Identify the Independent Variable |
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235 | (1) |
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Step 4 Identify and Describe the Dependent Variable |
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235 | (1) |
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Step 5 Choose the Right Statistical Test |
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236 | (1) |
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Step 6 Use Data Analysis Software to Test the Hypothesis |
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236 | (1) |
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Just in Case---A Nonparametric Alternative |
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237 | (1) |
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237 | (1) |
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Do You Understand These Key Words and Phrases? |
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237 | (1) |
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Do You Understand These Formulas? |
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237 | (1) |
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238 | (1) |
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The Case of Technology and Achievement |
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238 | (1) |
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The Case of Worrying about Our Neighbors |
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239 | (1) |
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240 | (1) |
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The Case of "We Can't Get No Satisfaction" |
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241 | (1) |
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The Case of "Winning at the Lottery" |
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242 | (2) |
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Chapter 9 Analysis Of Variance And Multivariate Analysis Of Variance |
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244 | (60) |
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244 | (1) |
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245 | (1) |
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The Different Types of ANOVAs |
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246 | (2) |
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246 | (1) |
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246 | (1) |
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Multivariate ANOVA (MANOVA) |
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247 | (1) |
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248 | (1) |
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248 | (1) |
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248 | (1) |
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Normal Distribution of Data |
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248 | (1) |
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248 | (1) |
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249 | (10) |
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249 | (2) |
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251 | (1) |
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252 | (1) |
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The Between Sum of Squares |
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253 | (1) |
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The Within Sum of Squares |
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253 | (2) |
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Computing the Degrees of Freedom |
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255 | (1) |
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Computing the Mean Square |
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255 | (1) |
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255 | (1) |
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256 | (1) |
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Determining the Area under the Curve for F Distributions |
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257 | (1) |
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258 | (1) |
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Effect Size for the ANOVA |
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258 | (1) |
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Testing a Hypothesis Using the ANOVA |
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259 | (15) |
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The Case of Multiple Means of Math Mastery |
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259 | (4) |
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263 | (1) |
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Multiple-Comparison Tests |
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263 | (1) |
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Always Observe the Means! |
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264 | (1) |
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The Case of Seniors Skipping School |
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265 | (3) |
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268 | (3) |
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The Case of Regional Discrepancies |
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271 | (3) |
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274 | (21) |
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The Case of Age Affecting Ability |
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275 | (7) |
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Interpreting the Interaction p Value |
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282 | (2) |
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284 | (3) |
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The Multivariate ANOVA (MANOVA) |
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287 | (1) |
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Assumptions of the MANOVA |
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288 | (1) |
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288 | (4) |
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The Case of Balancing Time |
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292 | (3) |
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295 | (1) |
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Do You Understand These Key Words and Phrases? |
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296 | (1) |
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Do You Understand These Formulas? |
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296 | (1) |
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296 | (1) |
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The Case of Degree Completion |
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296 | (1) |
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The Case of Seasonal Depression |
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297 | (2) |
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299 | (1) |
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300 | (1) |
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The Case of Employee Productivity |
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301 | (3) |
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Chapter 10 The Chi-Square Tests |
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304 | (31) |
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304 | (1) |
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The One-Way Chi-Square Test |
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304 | (1) |
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The Factorial Chi-Square Test (the Chi-Square Test of Independence) |
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305 | (13) |
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Computing the Chi-Square Statistic |
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306 | (1) |
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The Chi-Square Distribution |
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307 | (2) |
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What about the Post-Hoc Test? |
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309 | (2) |
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Working with an Even Number of Expected Values |
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311 | (2) |
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The Case of the Belligerent Bus Drivers |
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313 | (3) |
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The Case of the Irate Parents |
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316 | (2) |
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The Chi-Square Test of Independence |
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318 | (9) |
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Computing Chi-Square for the Test of Independence |
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319 | (1) |
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Computing Expected Values for the Test of Independence |
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319 | (1) |
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Computing the Chi-Square Value for the Test of Independence |
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320 | (1) |
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Determining the Degrees of Freedom for the Test of Independence |
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321 | (1) |
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We Are Finally Going to Test Our Hypothesis |
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321 | (1) |
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Using SPSS to Check What We Just Computed |
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322 | (2) |
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The Case of Corporal Punishment |
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324 | (3) |
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Post-Hoc Tests Following the Chi-Square |
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327 | (3) |
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The Case of Type of Instruction and Learning Style |
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327 | (3) |
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330 | (1) |
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Do You Understand These Key Words and Phrases? |
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330 | (1) |
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Do You Understand These Formulas? |
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330 | (1) |
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331 | (1) |
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The Case of Prerequisites and Performance |
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331 | (1) |
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The Case of Getting What You Asked For |
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332 | (1) |
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The Case of Money Meaning Nothing |
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332 | (1) |
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The Case of Equal Opportunity |
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333 | (2) |
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Chapter 11 The Correlational Procedures |
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335 | (40) |
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335 | (1) |
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Understanding the Idea of Correlations |
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335 | (4) |
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339 | (5) |
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340 | (1) |
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An Even More Important Word of Caution! |
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341 | (3) |
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A Nonparametric Correlational Procedure |
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344 | (14) |
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The p Value of a Correlation |
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345 | (1) |
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The Case of the Absent Students |
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346 | (4) |
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Another Example: The Case against Sleep |
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350 | (3) |
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The Case of Height versus Weight |
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353 | (2) |
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The Case of Different Tastes |
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355 | (3) |
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Once We Have a Linear Relationship, What Can We Do with It? |
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358 | (1) |
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358 | (12) |
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358 | (1) |
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359 | (2) |
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361 | (4) |
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Why Wasn't It Exactly Right? |
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365 | (2) |
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Using the Six-Step Model: The Case of Age and Driving |
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367 | (3) |
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370 | (1) |
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Do You Understand These Key Words and Phrases? |
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370 | (1) |
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Do You Understand These Formulas? |
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371 | (1) |
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371 | (1) |
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The Case of "Like Father, Like Son" |
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371 | (1) |
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The Case of "Can't We All Just Get Along?" |
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372 | (1) |
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The Case of More Is Better |
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373 | (1) |
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The Case of More Is Better Still |
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374 | (1) |
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Conclusion: Have We Accomplished What We Set Out to Do? |
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375 | (2) |
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Statistics in a New Light |
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375 | (1) |
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A Limited Set of Statistical Techniques |
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375 | (1) |
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The Use of Statistical Software Packages |
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376 | (1) |
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A Straightforward Approach |
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376 | (1) |
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376 | (1) |
Appendix A Area under the Normal Curve Table (Critical Values of z) |
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377 | (1) |
Appendix B Critical Values of t |
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378 | (1) |
Appendix C Critical Values of F When Alpha = .01 |
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379 | (2) |
Appendix D Critical Values of F When Alpha = .05 |
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381 | (2) |
Appendix E Critical Values of F When Alpha = .10 |
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383 | (2) |
Appendix F Critical Values of Chi-Square |
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385 | (1) |
Appendix G Selecting the Right Statistical Test |
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386 | (1) |
Glossary |
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387 | (10) |
Answers to Quiz Time! |
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397 | (24) |
Index |
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421 | (12) |
About the Author |
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433 | |