Inferential Statistics

Descriptive Statistics

Involves organizing, summarizing, simplifying, and presenting data to describe it.

Inferential Statistics

Focuses on generalizing from samples, testing hypotheses, and examining relationships between variables to make predictions.

Null Hypothesis

Refers to the null condition, indicating no difference between means or no relationship between variables.

Probability

The study of obtaining a sample from a population.

Probability

The study of patterns of random processes.

Probability Theory

The mathematical framework used for making decisions and drawing statistical conclusions based on the likelihood of different outcomes.

Statistical Inference

Drawing conclusions or making predictions about a population based on sample data using probability theory.

Statistical Inference

The use of statistics to assess the likelihood that our conclusions or predictions are accurate.

Random Selection

The process where each individual has an equal opportunity to be chosen, enhancing the representativeness of a sample.

Sampling Distributions

Theoretical distributions created to manage statistical results from different sample sizes and understand their relative frequencies.

Type I error

Incorrectly rejecting a true hypothesis

Type II error

Incorrectly accepting a false hypothesis

Parametric Measures of Association

Statistical tools that determine if there is a relationship between two variables within a specific population.

Correlation

Degree of relationship between two variables, answering the question "What is the degree of relationship between “x” and “y”?"

Parametric tests of significance

Statistical tests used when there are at least 30 observations, variables are on an interval scale, and the population is assumed to be normally distributed.

Parametric Measures of Association

Statistical tools used to assess the relationship between variables in a defined population.

t-test

A statistical test used for comparing means between two groups with sample sizes of 30 or fewer.

Paired T-tests

Statistical tests used to compare the means of a continuous variable in two non-independent samples.

Correlation

A statistical method used to determine the association or relationship between two continuous variables.

Correlation

Indicates if a linear relationship exists between two variables and measures the strength of that relationship.

Mann-Whitney U test

A non-parametric statistical test used as an alternative to the independent t-test.

Wilcoxon Matched Pairs test

A statistical test used as an alternative to the paired t-test for analyzing repeated measures on the same individual.

Kendall’s Tau

A measure used with ordinal data and ranking that considers ties, making it superior to Gamma.

Gamma

A measure used with ordinal data to forecast the rank of one variable based on the rank of another variable.

Lambda

A measure applicable with nominal data, where knowing the Independent Variable (IV) aids in making better predictions of the Dependent Variable (DV) compared to having no knowledge.

Kendall’s Tau

A measure used with ordinal data and ranking that considers ties, making it superior to Gamma.

Gamma

A measure used with ordinal data to forecast the rank of one variable based on the rank of another variable.

Lambda

A measure applicable with nominal data, where knowing the Independent Variable enhances the prediction of the Dependent Variable compared to having no knowledge.