Data Analysis – Simple Regression

These flashcards cover key concepts and terminology related to simple regression analysis as discussed in the lecture.

Correlation

Measures the strength of the linear relationship between two variables.

Causation

A relationship where one event causes another to occur.

Pearson Correlation

Used for interval and ratio scaled measures to determine correlation.

Spearman’s rank order Correlation

Used for ordinal scaled measures to determine correlation.

Correlation Coefficient (r)

A statistical measure that describes the degree of relationship between two variables, ranging from -1 to +1.

Regression Analysis

A statistical process for estimating the relationships among variables.

Dependent Variable (Y)

The variable that is being predicted or explained in regression analysis.

Independent Variable (X)

The variable that is used to predict the dependent variable in regression analysis.

Simple Regression

A regression analysis that uses one independent variable to predict the dependent variable.

Multiple Regression

A regression analysis that uses two or more independent variables to predict the dependent variable.

R-Square (R²)

A statistical measure that represents the proportion of the variance for the dependent variable that's explained by the independent variable(s).

F Ratio

A ratio used to determine the statistical significance of an overall regression model.

Beta Coefficient (β)

Indicates how much the dependent variable changes for each unit change in the independent variable.

t-statistic

A ratio used in hypothesis testing to determine if there is a significant difference between group means.

p-value

A value that helps determine the significance of results in hypothesis testing.

Predicted Regression Output

The expected value of the dependent variable based on the regression model and its coefficients.

Null Hypothesis (H0)

A statement indicating no effect or no relationship, which is tested against an alternative hypothesis.

Alternative Hypothesis (Ha)

A statement indicating the presence of an effect or a relationship, contrary to the null hypothesis.