About This Chapter
Below is a sample breakdown of the Statistics in Psychological Research 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||Statistics and statistical analysis||Scientific method, hypothesis and data; descriptive and inferential statistics|
|Tuesday||Descriptive statistics and measures of central tendency||Parts and statistics in a descriptive data set; standard deviation, variance, frequency distribution, histogram, mean, median and mode|
|Wednesday||Measures of variability and inferential statistics||Range, standard deviation and variance; types of inferential statistics, T-tests, analysis of variance and p-value|
|Thursday||Hypothesis testing and statistical significance||Comparing the null and alternative hypothesis; basic principle of statistical significance, critical regions, type I and type II errors|
|Friday||Psychological tests||Standardization and norms; types of tests, psychological measurement, norm-referenced tests and criterion-referenced tests|
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. 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.
3. What Are Descriptive Statistics? - Definition and Uses
This lesson is a simple walk-through of the common types of descriptive statistics and why they are important for understanding psychological research. You will likely be familiar with many of them but some you may not be.
4. Frequency Distributions: Definition & Types
This lesson explores the process of creating frequency distributions and histograms to give readers of your future scientific articles a numerical or visual way to understand the data you have presented.
5. Mean, Median & Mode: Measures of Central Tendency
By describing the data using central tendency, a researcher and reader can understand what the typical score looks like. In this lesson, we will explore in more detail these measures of central tendency and how they relate to samples and populations.
6. Measures of Variability: Range, Variance & Standard Deviation
Looking specifically at range, variance, and standard deviation, this lesson explores the relationship between these measures and samples, populations, and what it says about your data.
7. Inferential Statistics for Psychology Studies
Psychology is a science, which means that in order to understand people's thoughts and behaviors, a basic understanding of statistics is necessary. Most psychology studies use inferential statistics. This lesson covers basic types of inferential statistics, as well as how to decide whether a hypothesis was supported by the results.
8. Hypothesis Testing: Comparing the Null & Alternative Hypothesis
This lesson explores the process of comparing the null and the alternative hypothesis, as well as how to differentiate between the two after your testing is done.
9. Statistical Significance: Definition, Levels & Critical Regions
This lesson explores the basic principle of statistical significance and why it is important to understand when performing nearly any statistical test.
10. Standardization and Norms of Psychological Tests
Many psychological tests, including intelligence tests, are about comparing your score to others' scores to see how you did. Watch this lesson to find out about two important concepts in psychology: standardization and norms.
11. Types of Tests: Norm-Referenced vs. Criterion-Referenced
What's the best way to score tests? In this lesson, we'll look at two major types of tests that are scored differently from each other: norm-referenced and criterion-referenced tests.
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