Biostats Final Exam Review

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50 Terms

1

ANOVA

A statistical method used for comparing the means of three or more groups.

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2

F Ratio

The ratio of variance between groups to the variance within groups; larger F ratios indicate a more likely significant ANOVA.

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3

Power

The probability of correctly rejecting a false null hypothesis.

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4

Effect Size

A measure of how much the group means differ from one another; can indicate small or large differences.

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5

One Way ANOVA

A design that involves one independent variable with three or more levels to compare group means.

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6

Two Way ANOVA

An analysis involving two independent variables, assessing both their main effects and interactions.

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7

Repeated Measures ANOVA

A method where each subject is tested under all experimental conditions, controlling for individual differences.

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8

Mixed Design ANOVA

An ANOVA that includes at least one independent factor and one repeated factor.

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9

Post Hoc Multiple Comparisons

Exploratory tests carried out after a significant ANOVA to determine which means are different.

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10

Chi Square

A statistical test used to assess the association between categorical variables and test the significance of proportions.

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11

Goodness of Fit

A test to determine if observed data fits a specified distribution or expected proportions.

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12

Standardized Residuals

Measures used to show which categories contribute most to the chi square value, highlighting variances from expected values.

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13

Correlation

A measure of association between two variables, indicating the strength and direction of their relationship.

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14

Correlation Coefficient

A numerical measure that assesses the strength and direction of the relationship between two variables, ranging from -1 to +1.

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15

Linear Regression

A method to predict the value of a dependent variable based on an independent variable, while assessing shared variance.

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16

Multiple Regression

A regression analysis involving multiple independent variables predicting one dependent variable.

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17

Odds Ratio

A measure indicating how much more likely an individual is to belong to a target group compared to a reference group.

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18

Null Hypothesis

The hypothesis that there is no effect or no difference, commonly denoted as H0.

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19

Alternative Hypothesis

The hypothesis that there is a significant effect or difference, typically denoted as H1.

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20

Type I Error

The error made when the null hypothesis is incorrectly rejected, also known as a false positive.

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21

Type II Error

The error made when the null hypothesis is incorrectly accepted, also known as a false negative.

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22

Statistical Significance

A determination that an observed effect in data is likely not due to random chance, typically assessed via p-values.

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23

p-value

The probability of observing data as extreme as the sample, assuming the null hypothesis is true.

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24

Factorial ANOVA

An analysis of variance that evaluates two or more independent variables at the same time.

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25

Interaction Effect

A situation in ANOVA where the effect of one independent variable on the dependent variable differs depending on the level of another independent variable.

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26

Assumption of Homogeneity

The assumption that different samples have similar variances; important for the validity of ANOVA results.

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27

Confidence Interval

A range of values derived from sample statistics that is likely to contain the population parameter.

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28

Statistical Power

The likelihood that a study will detect an effect when there is an effect to be detected.

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29

Sample Size

The number of observations or replicates included in a statistical sample.

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30

Parametric Test

Statistical tests that assume data comes from a type of probability distribution and generally require interval data.

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31

Non-parametric Test

Statistical tests not based on parameterized family of probability distributions; useful for ordinal data.

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32

Corrected p-value

p-value adjusted to account for multiple testing errors, often using methods like Bonferroni correction.

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33

Control Group

The group in an experimental study that does not receive the treatment being tested, used for comparison.

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34

Experimental Group

The group in a study that receives the treatment or intervention being tested.

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35

Random Assignment

The process of randomly assigning participants to different experimental groups to reduce bias.

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36

Moderator Variable

A variable that affects the strength or direction of the relation between an independent and dependent variable.

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37

Mediator Variable

A variable that explains the relationship between the independent and dependent variables.

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38

Longitudinal Study

Research that follows the same subjects over a period of time to observe changes and developments.

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39

Cross-sectional Study

A study that analyzes data from a population at a specific point in time.

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40

Descriptive Statistics

A summary of the basic features of a dataset, providing simple summaries about the sample and measures.

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41

Inferential Statistics

Statistical methods that allow us to use sample data to make generalizations about a population.

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42

Outliers

Data points that differ significantly from the rest of the data, which can affect statistical analyses.

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43

Normal Distribution

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

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44

Skewness

A measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.

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45

Kurtosis

A descriptor of the shape of the probability distribution of a real-valued random variable, indicating tails and peak.

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46

Confidence Level

The percentage of times you can expect to get the same result if you were to repeat the same test numerous times.

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47

Sampling Bias

A bias in selecting a sample that is not representative of the population being studied.

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48

Response Bias

A tendency for respondents to answer questions inaccurately, often influenced by the wording of questions.

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49

Reliability

The consistency of a measure or test across time and contexts.

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50

Validity

The extent to which a test measures what it is purported to measure.

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