Biostatistics Review Class Notes

These flashcards cover key concepts and definitions related to central limit theorem, hypothesis testing, confidence intervals, and statistical significance in biostatistics.

Central Limit Theorem (CLT)

The theorem that states, for a sufficiently large sample size (n), the distribution of sample means is normally distributed.

Standard Error

The standard deviation of the sampling means.

95% Confidence Interval

An interval estimate that is likely to include the population parameter 95% of the time.

Z-score

A measure that describes a value's relation to the mean of a group of values, usually expressed in terms of standard deviations from the mean.

P-value

A statistical measure that helps to determine the significance of results in hypothesis testing.

Alpha (α)

The threshold p-value that determines whether to reject the null hypothesis, commonly set at 0.05.

Null Hypothesis (H0)

The hypothesis that there is no effect or no difference; used as a default position in statistical testing.

Alternative Hypothesis (H1)

The hypothesis that indicates the presence of an effect or a difference; it is what the researcher aims to support.

Histogram

A graphical representation of the distribution of numerical data using bars.

QQ Plot

A quantile-quantile plot that compares the quantiles of a sample distribution to the quantiles of a theoretical distribution.

Central Limit Theorem (CLT)

The theorem that states, for a sufficiently large sample size (n), the distribution of sample means is normally distributed.

Standard Error

The standard deviation of the sampling means.

95% Confidence Interval

An interval estimate that is likely to include the population parameter 95% of the time.

Z-score

A measure that describes a value's relation to the mean of a group of values, usually expressed in terms of standard deviations from the mean.

P-value

A statistical measure that helps to determine the significance of results in hypothesis testing.

Alpha (α)

The threshold p-value that determines whether to reject the null hypothesis, commonly set at 0.05.

Null Hypothesis (H0)

The hypothesis that there is no effect or no difference; used as a default position in statistical testing.

Alternative Hypothesis (H1)

The hypothesis that indicates the presence of an effect or a difference; it is what the researcher aims to support.

Histogram

A graphical representation of the distribution of numerical data using bars.

QQ Plot

A quantile-quantile plot that compares the quantiles of a sample distribution to the quantiles of a theoretical distribution.

Type I Error

The error of rejecting the null hypothesis when it is actually true. It is often denoted by alpha (\alpha).

Type II Error

The error of failing to reject the null hypothesis when it is false. It is often denoted by beta (\beta).

Population

The entire group of individuals, objects, or data points that a researcher is interested in studying.

Sample

A subset of individuals or data points selected from a population, used to make inferences about the entire population.

Sampling Distribution

The probability distribution of a statistic (e.g., sample mean) obtained from a large number of samples drawn from a specific population.