About This Chapter
Below is a sample breakdown of the Psychological Statistics, Tests and Measurement chapter into a 5-day school week. Based on the pace of your course, you may need to adapt the lesson plan to fit your needs.
|Day||Topics||Key Terms and Concepts Covered|
|Monday||Intro to Statistics, Tests and Measurement||Use of the scientific method and controls in psychology|
|Tuesday||Types of Research Designs in Psychology||Explanation of the three main types of research designs used in psychology|
|Wednesday||Reliability and Validity||Description of the reliability and validity requirements for psychological experiments|
|Thursday||Statistical Analysis: Descriptive Statistics||Overview of statistical analysis; use of averages in descriptive analysis, including, mean, median and mode|
|Friday||Statistical Analysis: Inferential Statistics||Use of inferential statistics to formulate conclusions and illustrate relationships among variables|
1. Introduction to Research Design & Statistical Analysis for Psychology
What do psychologists have to think about when designing studies and interpreting results? In this lesson, you'll explore how the scientific method can help with the difficult task of studying behaviors and their potential causes.
2. Types of Research Designs in Psychology
What are the three main research designs, and what are their advantages and disadvantages? In this lesson, you'll explore the different goals behind descriptive, correlational and experimental research designs.
3. Reliability & Validity in Psychology: Definitions & Differences
How do validity and reliability contribute to study design in psychology? In this lesson, you'll look at how experiments can fail reliability and validity requirements to get an idea of the challenges behind conducting significant psychological research.
4. Statistical Analysis for Psychology: Descriptive & Inferential Statistics
What are the two main types of statistics used by psychologists? In this lesson, you'll start to see what psychologists need to do to analyze their data and test the significance of their results.
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