Hypothesis Testing in Biostatics & Epidemiology
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These flashcards cover key vocabulary terms and concepts related to hypothesis testing, t-tests, ANOVA, and statistical reliability.
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30 Terms
Independent Samples
Two sample values from different populations that are not related or matched.
Dependent Samples
Sample values that are related, matched by some inherent relationship, such as before/after data.
Null Hypothesis (H0)
A statement that there is no effect or difference, often tested against an alternative hypothesis.
t-Test
A statistical test used to determine if there is a significant difference between the means of two groups.
Significance Level (alpha)
The probability of rejecting the null hypothesis when it is true, commonly set at 0.05.
Type I Error
The error made when a true null hypothesis is incorrectly rejected.
p-value
The probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true.
ANOVA (Analysis of Variance)
A statistical method used to test differences between two or more means by analyzing variance.
Post Hoc Tests
Tests conducted after an ANOVA to determine which specific group means are different.
Homogeneity of Variance
An assumption that the variances of different groups are equal.
Degrees of Freedom (df)
A parameter used in various statistical tests to determine the number of independent values.
Sphericity
The assumption that the variances of the differences between all combinations of related groups must be equal.
Cronbach’s Alpha
A measure of internal consistency or reliability of a set of items in a test.
Independent Samples
Two sample values from different populations that are not related or matched.
Dependent Samples
Sample values that are related, matched by some inherent relationship, such as before/after data.
Null Hypothesis (H0)
A statement that there is no effect or difference, often tested against an alternative hypothesis.
t-Test
A statistical test used to determine if there is a significant difference between the means of two groups.
Significance Level (alpha)
The probability of rejecting the null hypothesis when it is true, commonly set at 0.05.
Type I Error
The error made when a true null hypothesis is incorrectly rejected.
p-value
The probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true.
ANOVA (Analysis of Variance)
A statistical method used to test differences between two or more means by analyzing variance.
Post Hoc Tests
Tests conducted after an ANOVA to determine which specific group means are different.
Homogeneity of Variance
An assumption that the variances of different groups are equal.
Degrees of Freedom (df)
A parameter used in various statistical tests to determine the number of independent values.
Sphericity
The assumption that the variances of the differences between all combinations of related groups must be equal.
Cronbach
as Alpha
A measure of internal consistency or reliability of a set of items in a test.
Levene's Test
A statistical test used to assess the equality of variances for a variable calculated for two or more groups, checking the assumption of homogeneity of variance.
Mauchly's Test of Sphericity
A statistical test used to evaluate whether the assumption of sphericity has been met in a repeated-measures ANOVA.
Bonferroni Correction
A method used in post hoc analysis to counteract the problem of multiple comparisons by adjusting the significance level (alpha) for each test.
Tukey's Honestly Significant Difference (HSD)
A post hoc test used after an ANOVA to determine which specific pairs of group means are significantly different from each other while controlling the family-wise error rate.