Tests Flashcards

1
Q

Category of statistical tests where data must be normally distributed, interval or ratio data, and independent. Need sample size >30.

A

Parametric tests

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2
Q

Category of statistical tests where there are no assumptions of normal distribution. Can be used with a small sample size, and with nominal or ordinal data.

A

Nonparametric tests

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3
Q

Parametric test that can be used to examine the relationship between variables

A

Pearson’s Correlation Coefficient (r)

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4
Q

Three types of regression analysis

A
  1. Linear regression
  2. Multiple regression
  3. Logistic regression
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5
Q

Regression analysis that examines between a single independent variable and a single interval- or ratio-level variable

A

Linear regression

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6
Q

Regression analysis that makes a prediction about how two or more independent variables affects the dependent variable

A

Multiple regression

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7
Q

Regression analysis that is used when a dependent variable is categorical. Generates an Odds Ratio (OR)

A

Logistic regression

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8
Q

Parametric test used to compare the mean of two different groups

A

Independent samples t-test

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9
Q

Parametric test used to compare the mean within the same group (ie. before and after an intervention)

A

Paired t-test

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10
Q

A non-parametric test used to compare medians between two independent groups. It assesses whether the distributions of the two groups are statistically different.

A

Mann-Whitney U-Test

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11
Q

A non-parametric test used to compare medians within paired or related samples. It evaluates whether there’s a significant difference between two paired observations or measurements.

A

Wilcoxon Ranked-Sign Test

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12
Q

A statistical test used to determine if there’s a significant association between categorical variables in a contingency table. It assesses whether the observed frequencies differ significantly from the expected frequencies under the null hypothesis of no association.

A

Chi-Square Test

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13
Q

A parametric statistical test used to compare means among three or more independent groups. It assesses whether there is a statistically significant difference in means across the groups.

A

ANOVA (Analysis of Variance)

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14
Q

A statistical technique that extends ANOVA by incorporating one or more continuous covariates (variables that are controlled for or adjusted) into the analysis.

A

ANCOVA

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15
Q

A non-parametric statistical test used to compare medians among three or more independent groups. It determines whether there are significant differences in medians across these groups, making it a non-parametric alternative to one-way ANOVA.

A

Kruskal-Wallis

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16
Q

A non-parametric statistical test used to compare medians within a related group or repeated measures. It assesses whether there are significant differences in medians across multiple measurements or conditions, making it a non-parametric alternative to repeated measures ANOVA.

A

Friedman’s ANOVA

17
Q

A statistical test used to assess the normality of a dataset’s distribution. It evaluates whether a sample comes from a normally distributed population. A significant result indicates that the data significantly deviate from a normal distribution.

A

Shapiro-Wilk

18
Q

Non-parametric measure of rank correlation, assessing the strength and direction of association between two variables.

A

Spearman correlation