Inferential Statistics|Legit essays

Posted: February 18th, 2023

PSYC 005: Research Methods


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Review Sheet: Chapter 13 – Inferential Statistics


Complete assignment:

1. Read all instructions atop each section or item as you go.

2. Type your answers into colored spaces provided.

3. Answer the following items based on the content of chapter 13, “Inferential Statistics” from your textbook.


1. In your own words, explain the purpose of null hypothesis testing. What is the role of sampling error?


2. A researcher compares the effectiveness of two forms of cognitive behavioral group therapy for social phobia using an independent-samples t-test. What would it mean for the research to commit a Type I error? What would it mean for the research to commit a Type II error?
3. In recent years, the field of psychology has been grappling with the replicability crisis. What does that mean? What has emerged in the field of psychological science that has helped increase the transparency of psychological research? What are your thoughts about why it might be difficult to replicate a finding in the study of human behavior and emotions?






After you finish:

1. Save your work (by clicking Save since you have the file already named).

2. Pay attention to where your document/work is saved.

3. Upload the document into through Turn It In.



Inferential statistics is a branch of statistics that involves using data from a sample to make inferences or conclusions about a population. This is done by analyzing and drawing conclusions based on the patterns and relationships found in the sample data, which can then be used to make inferences about the larger population from which the sample was drawn.

Inferential statistics involves using probability theory and statistical inference techniques, such as hypothesis testing and confidence intervals, to make predictions and draw conclusions about the population. It is commonly used in research and experimental studies to test hypotheses, make predictions, and determine the statistical significance of relationships between variables.

Inferential statistics is a powerful tool for understanding the relationships and patterns in large data sets and can be used to make informed decisions and predictions about future outcomes. However, it is important to use appropriate statistical methods and to understand the limitations of the data and statistical techniques being used in order to draw accurate conclusions.

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