| |
| |
| |
| An Introduction to Statistics and Research Design: The Elements of Statistical Reasoning | |
| |
| |
| Two Branches of Statistics: Growing Our Knowledge about Human Behavior | |
| |
| |
| Descriptive Statistics: Organizing, Summarizing, and Communicating Numerical Information | |
| |
| |
| Inferential Statistics: Using Samples to Draw Conclusions about a Population | |
| |
| |
| Distinguishing Between a Sample and a Population | |
| |
| |
| Variables: Transforming Observations into Numbers | |
| |
| |
| Independent and Dependent Variables: The Main Ingredients of Statistical Thinking | |
| |
| |
| Putting Variables to Work: Independent, Dependent, and Confounding Variables | |
| |
| |
| Developing and Assessing Variables: The Reliability and Validity of Tests | |
| |
| |
| An Introduction to Hypothesis Testing: From Hunch to Hypothesis | |
| |
| |
| Types of Research Designs: Experiments, Non-Experiments, and Quasi-Experiments | |
| |
| |
| Experiments and Causality: Control the Confounding Variables | |
| |
| |
| Research Designs Other than Experiments: Non-Experiments and Quasi-Experiments | |
| |
| |
| One Goal, Two Strategies: Between-subjects Designs vs. Within-subjects Designs | |
| |
| |
| Curiosity, Joy, and the Art of Research Design | |
| |
| |
| Digging Deeper Into the Data: Variations on Standard Research Designs | |
| |
| |
| Outlier Analyses: Does the Exception Prove the Rule? | |
| |
| |
| Archival Studies: When the Data Already Exist | |
| |
| |
| |
| Descriptive Statistics: Organizing, Summarizing, and Graphical Individual Variables | |
| |
| |
| Organizing Our Data: A First Step in Identifying Patterns | |
| |
| |
| Distributions: Four Different Ways to Describe Just One Variable | |
| |
| |
| Applying Visual Depictions of Data: Generating Research Questions | |
| |
| |
| Central Tendency: Determining the Typical Score | |
| |
| |
| The Need for Alternative Measures of Central Tendency: Bipolar Disorder | |
| |
| |
| Mean: The Arithmetic Average | |
| |
| |
| Median: The Middle Score | |
| |
| |
| Mode: The Most Common Score | |
| |
| |
| The Effect of Outliers on Measures of Central Tendency | |
| |
| |
| An Early Lesson in Lying With Statistics: Which Central Tendency is "Best?" | |
| |
| |
| Measures of Variability: Everyone Can't Be "Typical" | |
| |
| |
| Range: From the Lowest to the Highest Score | |
| |
| |
| Variance: The First Step in Calculating Standard Deviation | |
| |
| |
| Standard Deviation: Variation from the Mean | |
| |
| |
| Shapes of Distributions: Applying the Tools of Descriptive Statistics | |
| |
| |
| Normal Distributions: The Silent Power Behind Statistics | |
| |
| |
| Skewed Distributions: When Our Data Are Not Symmetrical | |
| |
| |
| Bimodal and Multimodal Distributions: Identifying Distinctive Populations | |
| |
| |
| Kurtosis and Distributions: Tall and Skinny Versus Short and Wide | |
| |
| |
| Digging Deeper into the Data: Alternate Approaches to Descriptive Statistics | |
| |
| |
| The Interquartile Range: An Alternative to the Range | |
| |
| |
| Statistics that Don't Focus on the Mean: Letting the Distribution Guide our Choice of Statistics | |
| |
| |
| |
| Visual Displays of Data: Graphs That Tell a Story | |
| |
| |
| Uses of Graphs: Clarifying Danger, Exposing Lies, and Gaining Insight | |
| |
| |
| Graphing in the Information Age: A Critical Skill | |
| |
| |
| "The Most Misleading Graph Ever Published": The Cost and Quality of Higher Education | |
| |
| |
| "The Best Statistical Graph Ever Created": Napoleon's Disastrous March to Moscow | |
| |
| |
| Common Types of Graphs: A Graph Designer's Building Blocks | |
| |
| |
| Scatterplots: Observing Every Data Point | |
| |
| |
| Line Graphs: Searching for Trends | |
| |
| |
| Bar Graphs: An Efficient Communicator | |
| |
| |
| Pictorial Graphs: Choosing Clarity over Cleverness | |
| |
| |
| Pie Charts: Are Pie Charts Pass�©? | |