"A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis."
Involves formulating a testable statement that predicts the relationship between variables in a study and evaluating the evidence to support or reject the hypothesis.
Null and Alternative Hypotheses: The null hypothesis is usually the theory that a researcher wants to disprove, while the alternative hypothesis is the claim that the researcher wants to support.
Type I and Type II Errors: Type I error occurs when the null hypothesis is rejected when it is actually true, while type II error occurs when the null hypothesis is not rejected even when it is false.
Significance Level: Significance level is the probability of encountering a type I error when no true difference between groups exists, typically set at α=0.05.
P-Value: The p-value is the probability of obtaining a sample result as extreme or more extreme than the observed result, assuming the null hypothesis is true.
Confidence Intervals: Confidence intervals are a range of values that reflect the possible values of a population parameter with a specified level of confidence.
One-sample T-test: A statistical test used to determine if a sample mean is significantly different from a hypothesized population mean.
Two-sample T-test: A statistical test used to determine if there is a statistically significant difference between the means of two independent samples.
One-way ANOVA: A statistical method used to compare the means of three or more independent groups.
Chi-Square Test: A statistical test used to determine if there is a significant association between two categorical variables.
Correlation and Regression Analysis: Correlation analysis examines the strength of a relationship between two continuous variables, while regression analysis is used to predict a dependent variable using one or more independent variables.
Power Analysis: Power analysis is the ability to detect a difference between groups if it exists, and this is usually in the context of understanding the amount of subjects required in each group to reach statistical significance.
One-sample t-test: Used to test the hypothesis that the mean of a single population equals a specified value.
Two-sample t-test: Used to test the hypothesis that the means of two populations are equal.
Paired t-test: Used to test the hypothesis that the means of two related populations (e.g., pre and post intervention measurements) are equal.
Analysis of variance (ANOVA): Used to test the hypothesis that the means of more than two populations are equal.
Chi-squared test: Used to test the hypothesis that two categorical variables are independent.
Fisher's exact test: Used when the sample size is small and the assumptions of the chi-squared test are not satisfied.
Wilcoxon rank-sum test: Used to compare the medians of two populations.
Kruskal-Wallis test: Used to compare the medians of more than two populations.
Mann-Whitney U test: Used to test the hypothesis that the distribution of one population is shifted to the right or left of the other population.
McNemar's test: Used to test the hypothesis that the proportion of matched pairs that have a discordant outcome is different between two groups.
Poisson regression: Used to test the hypothesis that the rate of occurrences of an event (e.g., number of accidents per day) is different between two or more groups.
Logistic regression: Used to test the hypothesis that the odds of an event occurring (e.g., developing a disease) are different between two or more groups.
Survival analysis: Used to test the hypothesis that the survival curves of two or more groups differ.
"A statistical hypothesis test is... used to decide whether the data at hand sufficiently support a particular hypothesis."
"Hypothesis testing allows us to make probabilistic statements about population parameters."
"A method of statistical inference [i.e., hypothesis testing] used to decide whether the data at hand sufficiently support a particular hypothesis."
"A statistical hypothesis test is a method... used to decide whether the data at hand sufficiently support a particular hypothesis."
"Hypothesis testing allows us to make probabilistic statements about population parameters."
"A statistical hypothesis test... used to decide whether the data at hand sufficiently support a particular hypothesis."
"Hypothesis testing allows us to make probabilistic statements about population parameters."
"A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis."
"A statistical hypothesis test is a method... used to decide whether the data at hand sufficiently support a particular hypothesis."
"A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis."
"A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis."
"A statistical hypothesis test is a method... used to decide whether the data at hand sufficiently support a particular hypothesis."
"A statistical hypothesis test is a method... used to decide whether the data at hand sufficiently support a particular hypothesis."
"A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis."
"A statistical hypothesis test is a method... used to decide whether the data at hand sufficiently support a particular hypothesis."
"Hypothesis testing allows us to make probabilistic statements about population parameters."
"A statistical hypothesis test is a method... used to decide whether the data at hand sufficiently support a particular hypothesis."
"A statistical hypothesis test... used to decide whether the data at hand sufficiently support a particular hypothesis."
"A statistical hypothesis test is a method... used to decide whether the data at hand sufficiently support a particular hypothesis."