Inferential Statistics Overview

Questions and Answers

What is inferential statistics?

Ways of analyzing data to make conclusions about a hypothesis (correct)

A form of descriptive statistics

A method to summarize data

A test to compare two averages

What does a t-test compare?

The average scores between two different groups in a study.

What does ANOVA stand for?

Analysis of Variance

What does the p-value indicate?

The likelihood that the study results occurred by random chance. Signup and view all the answers

How sure do psychologists need to be to accept a hypothesis?

95% sure Signup and view all the answers

What do inferential statistics help psychologists do?

Decide whether hypotheses are supported by study results. Signup and view all the answers

Study Notes

Inferential Statistics

Analyzes data to draw conclusions regarding hypothesis support.
Derived from the term 'inference,' indicating drawing conclusions from environmental clues.

t-test

Compares average scores of two different groups in a study.
Applicable for naturally occurring groups (e.g., boys vs. girls) or created groups in experiments.

Analysis of Variance (ANOVA)

Compares average scores among three or more groups to determine differences.
Functions similarly to a t-test but allows analysis of multiple groups simultaneously.

p-value

Results from statistical tests like correlation, t-tests, or ANOVA.
Indicates the probability that study results occurred by random chance.

Hypothesis Support Confidence

Psychologists generally accept a maximum of 5% chance (p-value ≤ 0.05) that results occurred due to random factors.
A p-value between 0.00 and 0.05 suggests a 95% confidence in the validity of results.

Summary of Key Concepts

Inferential statistics help determine hypothesis support in psychology studies.
t-tests are for two groups; ANOVA is for three or more.
A p-value of 0.05 or less indicates significant results, reducing chances of random occurrence.

Description

This quiz covers key concepts in inferential statistics, including t-tests, ANOVA, and p-values. You'll learn how these statistical methods help analyze data to draw conclusions and understand the probability of results. Test your knowledge about hypothesis support and the significance of statistical findings.