Inferential Statistics: T Test ANOVA, Correlation, Chi Square, Simple Multiple & Logistic Regression | Summary and Q&A

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February 18, 2024
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Solomon Getachew
Inferential Statistics: T Test ANOVA, Correlation, Chi Square, Simple Multiple & Logistic Regression

TL;DR

Inferential statistics is used to draw conclusions about a population based on sample data, and it can be categorized into tests and ANOVA, correlation and K Square, and regression analysis.

Key Insights

• โ Descriptive analysis is used to summarize and describe a sample, while inferential statistics make inferences about a population.
• ๐ Inferential statistics can be categorized into tests and ANOVA, correlation and K Square, and regression analysis.
• ๐ Tests and ANOVA compare groups or variables, correlation and K Square examine relationships, and regression analysis predicts a variable based on other variables.
• ๐ป Logistic regression is used when the dependent variable is categorical, and multiple regression allows for the inclusion of multiple independent variables.
• ๐งก The correlation coefficient ranges from -1 to 1 and indicates the strength and direction of the relationship between variables.
• ๐ Spearman rank correlation is used when the relationship between variables is not linear and the variables are of ordinal level of measurement.
• ๐ K Square test is used to find the association between two categorical variables.

Transcript

hello and welcome to lesson 30 inferential statistics in lesson 29 as you remember we have discussed about descriptive analysis descriptive analysis is the most basic data analysis which is used to summarize and describe the main features of the sample and which is also used to identify pattern Trends and provide conclusion about the sample it is c... Read More

Q: How does inferential statistics differ from descriptive analysis?

Descriptive analysis summarizes and describes a sample, while inferential statistics make inferences about a population based on that sample.

Q: What are the three categories of inferential statistics?

The three categories are tests and ANOVA, correlation and K Square, and regression analysis.

Q: What is the purpose of tests and ANOVA in inferential statistics?

Tests and ANOVA are used to compare groups or variables and determine if there is a significant difference between their means.

Q: How does logistic regression differ from simple and multiple regression?

Logistic regression is used when the dependent variable is categorical, while simple and multiple regression are used when the dependent variable is continuous.

Q: What is the range of the correlation coefficient?

The correlation coefficient ranges from -1 to 1, where values close to -1 or 1 indicate a strong correlation, values close to 0 indicate a weak correlation, and 0 indicates no correlation.

Q: When is Spearman rank correlation used?

Spearman rank correlation is used when the relationship between variables is not linear and the variables are of ordinal level of measurement.

Q: What is the purpose of K Square test in inferential statistics?

K Square test is used to find the association between two categorical variables and determine if there is a significant difference in their proportions.

Q: How does multiple regression differ from simple regression?

Multiple regression allows for the inclusion of two or more independent variables, while simple regression only uses one independent variable.

Summary & Key Takeaways

• Descriptive analysis is used to summarize and describe the main features of a sample, while inferential statistics is used to make inferences about a population based on that sample.

• There are three categories of inferential statistics: tests and ANOVA, correlation and K Square, and regression analysis.

• Tests and ANOVA are used to compare groups or variables, correlation and K Square examine relationships between groups or variables, and regression analysis predicts a variable based on other variables.