About This Chapter
Research Methods & Statistics - Chapter Summary
If you want to improve your knowledge on research methods and statistics, these lessons will be very helpful. Some topics you will study include qualitative research and factor analysis. You'll review key vocabulary words and see examples of qualitative research and inferential statistics. Topics covered include:
- How to draw a sample
- Different types of research such as quasi-experimental research and case studies
- Ideas behind randomized experimental design
- Three ways to conduct research on adults
- Sources of qualitative data
- Understanding psychological research
- Use of inferential statistics
- Types of probability sampling
- Meta-analysis research
- Benefits and consequences to collecting data
- Types of factor analyses
- Parametric vs. non-parametric methods
Our informative and engaging lessons are also quick, lasting no longer than 10 minutes, and are taught by professional instructors who are experts in their field. With features like the timeline feature and transcripts, it is easy to review just the parts that discuss topics you are struggling to understand, saving you time and enhancing your studying experience.
1. What is Sampling in Research? - Definition, Methods & Importance
The sample of a study can have a profound impact on the outcome of a study. In this lesson, we'll look at the procedure for drawing a sample and why it is so important to draw a sample that represents the population.
2. Research Designs: Quasi-Experimental, Case Studies & Correlational Research Designs
The true experiment is not the only way to conduct research. This lesson will help you understand the use of quasi-experimental research designs, case studies, and correlational research.
3. How Randomized Experiments Are Designed
When reading research or when conducting your own, it is important to understand the basic concepts of randomized experimental design that are covered in this lesson.
4. Cross-sectional, Longitudinal & Sequential Designs: Advantages & Disadvantages
This lesson examines the three main ways of conducting research on adults and older individuals. Specifically, we will examine the three types, some of their advantages, and some of their disadvantages.
5. What is Qualitative Research? - Definition, Sources & Examples
Sometimes research does not involve simple numbers that you can analyze. When that happens, where do researchers get their data? In this lesson, we'll look at qualitative data and the major sources of it.
6. 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.
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. Probability Sampling Methods: Definition & Types
Choosing a sample is one of the most important steps in research. But how should you choose? In this lesson, we'll look at three types of probability sampling: simple random, systematic, and stratified sampling.
9. Using Archival Research & Secondary Records to Collect Social Research Data
This lesson explores the idea of what happens when researchers already have information and data that they can study. You'll get the chance to look at descriptions of archival and meta-analysis research.
10. Using Surveys to Collect Social Research Data
There are many techniques to collect information from people. In this lesson, we will explore some of the ways a researcher collects data, as well as looking at some of the risks and benefits.
11. Factor Analysis: Confirmatory & Exploratory
A factor analysis is a statistical procedure that is used in order to find underlying groups of related factors in a set of observable variables. Learn about the different types of factor analyses and more.
12. Non-Parametric Inferential Statistics: Definition & Examples
In this lesson, you're going to learn about the major differences between parametric and non-parametric methods for dealing with inferential statistics, as well as see an example of the non-parametric method.
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