Correlation and t-Tests Study Guide

Flashcards encompassing key vocabulary and concepts from the lecture notes on correlation, probability, and t-tests.

Correlation

The measure of the strength and direction of the relationship between two variables.

Scatterplot

A graph used to show the relationship between two variables, with points representing paired values of X and Y.

Regression Equation

The equation Y = bX + a, where Y is the predicted variable, X is the predictor variable, b is the slope, and a is the Y-intercept.

Positive Relationship

A relationship where both X and Y increase together.

Negative Relationship

A relationship in which Y decreases as X increases.

Pearson's r

A correlation coefficient that measures the strength and direction of linear relationships, used with interval or ratio data.

Coefficient of Determination (r²)

The proportion of variance in the dependent variable that is explained by the independent variable.

Independent Events

Events where the occurrence of one does not affect the probability of the other.

Dependent Events

Events where the occurrence of one affects the probability of the other.

t Test

A statistical test used to determine if there is a significant difference between the means of two groups.

Degrees of Freedom (df)

The number of independent values that can vary in an analysis without breaking any constraints.

Assumption of Normality

The assumption that the data follows a normal distribution, which is particularly important for small sample sizes.

Cohen's d

A measure of effect size that indicates the standardized difference between two means.

Sampling Distribution

The distribution of all possible sample means from a population.

Standard Error (SE)

The standard deviation of the sampling distribution of the mean.

Z-test Assumptions

The requirements for conducting a z-test, including that the population standard deviation is known and the sample size is sufficiently large.