Central Limit Theorem
Sampling distribution of the sample mean approximates a normal distribution as sample size increases
Chi-Square Goodness of Fit Test
Tests if sample distribution fits a population distribution
Addition Rule for Probability
P(A or B) = P(A) + P(B) - P(A and B)
Correlation Coefficient
Measures strength and direction of linear relationship between two variables
Box Plot
Displays five-number summary (minimum, Q1, median, Q3, maximum)
Coefficient of Determination
R-squared; proportion of variance in the dependent variable predictable from the independent variable
Chi-Square Test for Independence
Tests if two categorical variables are independent
Cumulative Frequency
Sum of frequencies for that category and all previous categories
Alternative Hypothesis
Statement researcher wants to prove
Blinding
Participants unaware of whether they are receiving treatment or placebo
Control Group
Group in an experiment that does not receive treatment
Categorical Data Analysis: Chi-square Test
Assesses relationships between categorical variables
Convenience Sampling
Use results that are easy to get
Bimodal Distribution
Distribution with two different modes
ANOVA (Analysis of Variance)
Compares means of three or more groups
Binomial Distribution
Probability distribution of number of successes in a fixed number of trials
Confounding Variable
Variable related to both the treatment and the outcome
Confidence Interval
Range of values believed to contain population parameter with a certain level of confidence
Biased vs Unbiased Estimator
Biased: systematically off; Unbiased: accurate on average
Combination
Selection of objects without regard to order
Bayes' Theorem
Calculates probability of an event based on prior knowledge of conditions
Conditional Probability Formula
P(A|B) = P(A and B)/P(B)
Cluster Sampling
Population divided into clusters; randomly select clusters, then sample all in cluster
Conditional Probability
Probability of an event occurring given another event has already occurred
Confounding vs Lurking Variable
Confounding: affects both variables; Lurking: affects outcome but not considered in analysis