Statistical Analysis and Interpretation

These flashcards cover key vocabulary terms and concepts related to statistical analysis and hypothesis testing, designed to aid in understanding and applying statistical principles.

Hypothesis

A proposed explanation for a phenomenon used as a starting point for further investigation and testing. It must be testable and falsifiable.

Null Hypothesis (H0)

The hypothesis that there is no effect or difference, and that any observed difference is due to sampling or experimental error. Often stated as 'no relationship' or 'no change'.

Alternative Hypothesis (Ha)

The hypothesis that there is an effect or difference, and that the observed results are not due to chance. It is what the researcher is trying to prove.

P-value

A p-value is the probability that the observed data would occur if the null hypothesis were true. A small p-value (typically <0.05) suggests evidence against the null hypothesis.

Confidence Interval (CI)

A range of values that is likely to contain the true population parameter with a specified probability, such as 95% or 99%.

Independent Samples Test

A statistical test used to determine whether there are significant differences between two independent groups, meaning the data points in one group are not related to the data points in the other group.

Regression Analysis

A statistical process for estimating the relationships among variables, typically involving a dependent variable and one or more independent variables, to predict outcomes or understand variable influence.

Odds Ratio (OR)

A measure of association used in case-control studies, representing the odds that an event will occur in an exposed group relative to an unexposed group. An OR of 1 indicates no association.

Rate Ratio (RR)

A measure that compares the rate of an event in two groups, often used in cohort studies, indicating how many times higher or lower the rate is in one group compared to another.

Effect Size

A quantitative measure of the magnitude of a phenomenon; commonly assessed in hypothesis testing to determine the practical significance of a finding, beyond just statistical significance.

Parametric Tests

Statistical tests that assume the data follows a specific distribution, usually Gaussian (normal distribution), and require interval or ratio data. Examples include t-tests and ANOVA.

Nonparametric Tests

Statistical tests that do not assume a specific distribution for the data and are often used for ordinal, nominal, or non-normally distributed interval/ratio data. Examples include the Mann-Whitney U test.

Bivariate Analysis

Statistical analysis that examines the relationship between two variables, such as correlation or simple regression, to understand their association.

Multivariate Analysis

Statistical analysis that involves multiple variables concurrently to understand their complex relationships, often used when examining confounding or multiple predictors.

Type I Error

The error of rejecting the null hypothesis when it is actually true. This is also known as a 'false positive' and its probability is denoted by \alpha .

Type II Error

The error of failing to reject the null hypothesis when it is false. This is also known as a 'false negative' and its probability is denoted by \beta .

Statistical Significance

A statistical statement of how likely it is that an obtained result occurred by chance; typically determined by a p-value below a preset alpha level (e.g., p < 0.05).

Cohen's d

A measure of effect size used to indicate the standardised difference between two means, allowing for comparison across different studies. Common interpretations are small (0.2), medium (0.5), and large (0.8).

Matched Pairs Test

A statistical test used to compare two groups or conditions where observations are dependent or 'matched' in specific characteristics, such as before-and-after measurements on the same subjects.

Case-Control Study

A study that compares individuals with a disease (cases) to those without the disease (controls) to find related factors or exposures by looking retrospectively.

Cohort Study

A study that follows a group of individuals (a cohort) over time to observe outcomes related to specific exposures, often used to study disease incidence and risk factors prospectively.

Intent to Treat Analysis

An analysis based on the initial treatment assignment of participants in a clinical trial, regardless of whether they completed the treatment or switched treatments, to preserve randomization benefits.