Statistics Lecture Notes

Flashcards covering key statistical concepts and definitions for exam review.

Standard Error

A measure that tells us how far a statistic is likely to be from the population parameter it estimates.

Bootstrapping

A resampling technique used to estimate statistics on a dataset by sampling with replacement.

Population Proportion (p)

The true proportion of a particular characteristic in a population.

Sample Size (n)

The number of observations in a sample.

Confidence Interval

A range of values used to estimate the true value of a population parameter.

Margin of Error

The amount that is allowed for in case of miscalculation or change of circumstances in the estimation of a population parameter.

Normal Distribution

A continuous probability distribution characterized by a bell-shaped curve, symmetric around the mean.

Critical Value (z*)

The value that represents the number of standard deviations a point is from the mean, used in constructing confidence intervals.

Variability

The degree to which data points in a statistical distribution differ from each other and the population mean.

Hypothesis Test

A method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis.

Randomization Distribution

A distribution of statistics obtained by performing random sampling.

Sampling Distribution

The probability distribution of a given statistic based on a random sample.

Bootstrap Distribution

The distribution of a statistic based on many resampled datasets from an original dataset, used to estimate the standard error.

p-hat (sample proportion)

An estimator of the population proportion calculated from sample data.

Conditions for Normal Approximation

If np >= 10 and n(1-p) >= 10, then the sampling distribution of the sample proportion can be approximated by a normal distribution.

Bimodal Distribution

A probability distribution with two different modes, or peaks.