About This Chapter
Statistical Analysis: Descriptive & Inferential Statistics - Chapter Summary
When conducting or interpreting special education research, it's important to have a strong grasp on statistical analysis. This chapter offers useful resources that can improve your ability to analyze descriptive and inferential statistics as a special education teacher. You can examine several types of analysis techniques and methods and develop skills to help you compare hypotheses, find data trends, examine statistical relationships and assess differences between research statistics.
You can also check your understanding of these techniques using the included self-assessment quizzes and comprehensive chapter exam. All of the chapter resources are accessible on any device that has an Internet connection so you can work through the material wherever it's convenient.
How It Helps
- Improves statistical analysis skills: These resources offer simple methods and techniques that help you properly analyze statistics.
- Strengthens special education research abilities: Cultivating these statistical analysis skills can help you better understand research in the field of special education and improve your instructional abilities.
- Helps you practice: The included self-assessments allow you to practice analyzing different types of statistics.
After competing the chapter, you should be able to:
- Analyze statistics using categorical data
- Apply effective statistical analysis techniques and methods
- Use data to examine relationships and locate trends
- Compare alternative and null hypotheses
- Evaluate the components of one-tailed, two-tailed, t-tests and chi-square tests
- Calculate and interpret an F-ratio
- Analyze multi-group variances using ANOVA
- Differentiate between statistical and clinical significance
- Interpret correlations and non-significant outcomes in research results
- Recognize generalization limits
1. 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.
2. Statistical Analysis with Categorical Data
Learn why percentages are so important when analyzing categorical data in this video lesson. Watch as the data is turned into a data table and a visual bar graph as ways to analyze the data.
3. Statistical Analysis: Methods & Techniques
Statistical analysis is the process of collecting and reading data so that one can describe past behavior and characteristics and predict future ones. This lesson will give the definition and formulas of different methods you can use.
4. Statistical Analysis: Using Data to Find Trends and Examine Relationships
Many different organizations use statistical analysis to describe and analyze data and to predict future trends. Learn about the different types of statistics in this video lesson.
5. 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.
6. One-Tailed Vs. Two-Tailed Tests: Differences & Examples
This lesson explores the difference between the one-tailed and two-tailed tests. We will look at what they mean in statistical testing, as well as when you should and should not use them.
7. What Are t-Tests? - Assessing Statistical Differences Between Groups
This lesson explores how a researcher may use a t-Test. In addition, simple to follow instructions will demonstrate how to manually complete a t-Test.
8. The Chi-Square Test
What if you expect one thing, but get another? The chi-square test is a method of statistical analysis that can help us identify if the results from a genetic cross are simply due to chance, or if something else is happening. Learn about the chi-square test in this lesson.
9. How to Calculate the F-Ratio
In statistics, the F-ratio is used to determine if there are differences between groups in an experiment. In this lesson, learn how to calculate the F-ratio and interpret the result.
10. Using ANOVA to Analyze Variances Between Multiple Groups
This lesson explores what an analysis of variance, or ANOVA, is and how you as a researcher may use it to find the difference between multiple levels of the same variable without doing a ton of T-tests.
11. Statistical Significance: Definition & Calculation
Watch this video lesson to learn about statistical significance, and how it relates to surveys and other real world events. Also, learn how it is calculated, and how you can describe it to others.
12. Interpreting a Non-Significant Outcome
Research can take a lot of time for the person conducting it. So what happens when the statistics show that the results are not significant? In this lesson, we'll look at what a non-significant outcome means and what it doesn't mean.
13. Clinical Significance vs. Statistical Significance
What does it mean if the results of a study are significant? In this lesson, we'll about the difference between statistical significance and clinical significance, and what this means for applying the results of research to the real world.
14. How to Interpret Correlations in Research Results
Perhaps the most common statistic you'll see from psychology is a correlation. Do you know how to correctly interpret correlations when you see them? This lesson covers everything you need to know.
15. Limits to Generalization of a Research Study
What happens if a research study confirms the researcher's hypothesis? In this lesson, we'll look at the limits of generalizing from a single research study, including the importance of representativeness and replicability.
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Other chapters within the Research Methods in Special Education course
- Research Foundations for Education
- Developing a Research Plan
- Data Collection Methods & Techniques
- Single-Subject Research Designs
- Experimental & Quasi-Experimental Designs
- Sampling and Generalization
- Overview of Measurement in Research
- Internal Validity in Research
- External Validity
- Qualitative Research Methods and Design
- Issues in Ethical Research