Hypotheses Testing (Part 2) - Testing Statistical Significance with Continuous Variables

These flashcards cover key concepts and terminology related to hypotheses testing, statistical methods for mean comparison, and the application of statistical tests like ANOVA.

Hypotheses Testing

A method used to make decisions or inferences about population parameters based on sample data.

Chi-Square Test

A statistical method used to determine if there is a significant association between two categorical variables.

One-sample t-test

A statistical test used to compare the mean of a single sample to a known value.

Two unrelated (independent) mean test

A method to compare the means of two independent groups.

Two related (dependent) mean test

A statistical test comparing means from the same group at different times or under different conditions.

Analysis of Variance (ANOVA)

A statistical method to compare the means of three or more groups to see if at least one group differs significantly from the others.

Null Hypothesis (H0)

The hypothesis that there is no significant difference between the means or groups being tested.

Alternative Hypothesis (Ha)

The hypothesis that there is a significant difference between the means or groups being tested.

Degrees of Freedom (df)

A parameter used in statistical tests to define the number of independent values or quantities which can be assigned to a statistical distribution.

t-statistics

A ratio of the departure of an estimated parameter from its hypothesized value to its standard error.