Inferential Statistics Lecture Review

These flashcards cover the fundamental terms and concepts from the lecture on inferential statistics, providing a quick review for exam preparation.

Inferential Statistics

A branch of statistics that deals with inference about populations based on sample data.

Null Hypothesis (H0)

A statement or assumption that there is no effect or no difference; it is what we aim to test against.

Alternative Hypothesis (H1/Ha)

The hypothesis that there is an effect or a difference; it represents what you want to prove.

Hypothesis Testing

A method of statistical inference used to determine the evidence against the null hypothesis.

Alpha Level (α)

The threshold level at which we reject the null hypothesis; commonly set at 0.05, 0.01, or 0.10.

Type I Error

The error made when a true null hypothesis is incorrectly rejected.

Type II Error

The error made when a false null hypothesis is not rejected.

Dependent Sample t-Test

Statistical test used to compare means from the same group at different times.

Independent Sample t-Test

Statistical test used to compare means from two independent groups.

One-Way ANOVA

A statistical method used to compare the means of three or more groups.

Chi-Square Test for Independence

A statistical test used to determine if two categorical variables are independent.

p-value

The probability value that helps determine the significance of results; if p ≤ α, reject the null hypothesis.

Pearson r

A statistic that measures the strength and direction of the linear relationship between two variables.

Normal Distribution

A probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence.

Sample

A subset of a population used for the purpose of making inferences about the population.

Observed Frequencies

The actual counts of occurrences in each category of a categorical variable.

Expected Frequencies

The counts we would expect in each category if the null hypothesis is true.

Graphical Methods for Normality

Tools like Q-Q plots or histograms used to assess if data follows a normal distribution.