Math 285: Business Statistics Lecture Review

These flashcards cover key concepts from the Business Statistics lecture, focusing on terms and definitions relevant to hypothesis testing, confidence intervals, and sampling methods.

Confidence Interval

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

Parameter of Interest

The specific quantity that a researcher aims to estimate, such as a population mean or proportion.

P-value

The probability of obtaining a test statistic as extreme as, or more extreme than, the one observed, assuming the null hypothesis is true.

Hypothesis Testing

A systematic method used to decide if the data at hand sufficiently support a particular hypothesis.

Sampling Distribution

The probability distribution of a statistic obtained by selecting random samples from a population.

Type 1 Error

The incorrect rejection of a true null hypothesis, also known as a false positive.

Type 2 Error

The failure to reject a false null hypothesis, also termed a false negative.

Explanatory Variable

A variable that is manipulated to observe its effect on a response variable in an experiment.

Categorical Variable

A variable that can take on one of a limited and usually fixed number of possible values, assigning each individual or other unit of observation to a particular group or nominal category.

Blocking Variable

A variable that is used to control for variability and reduce confounding effects in an experimental design.