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### 18 Cards in this Set

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 r Correlation Coefficient Measure of strength and direction of the linear relationship between 2 quantitative variables Simple Random Sample (SRS) An SRS of size n is chosen by a method where every possible group of n has an equal likelyhood of being chosen. Experimental Design Principle -Control= for lurking variables, ensure that only systematic differences occur in treatments -Random assignment= treatments are randomly assigned to experimental units -Replication= enough experimental units are used in each group so effects can be distinguished Random Variable Probability Distribution The list of outcomes, possible values, and probabilities Random Variable Numerical result of a random phenomenon Sampling Distribution Distribution of values taken by the statistic in all possible samples of the same size from the same population Binomial Setting -Binary= possible outcome a "success" or "failure" -Independent= results don't effect each other -Number= number of trials n is defined -Success= probability of success for each trial is the same Outlier in Distribution An observation is an outlier if it falls more than 1.5xIQR above Q3 or below Q1 Density Curve -Always above or on the x axis -Area under curve=1 Residual DIfference between the observed y and the predicted y (y-y-hat) Least Squares Regression LSR of y on x is the line that makes the sum of the squared residuals as small as possible r-squared Coefficient of Determination % variability y explained by a linear relationship to x Outlier in a Regression An observation that lies outside overall pattern of the other observations. Points are outliers in the y direction but not x have large residuals, others may not. Influential Point If point was removed it would change result of the calculation. Outliers in the x direction. Independence A and B are independent if knowing one occurs tells you nothing about the other Parameter Constant that describes the population Statistic Random variable that describes a sample (used to estimate parameters) N>10n condition Population (N) must be more than 10 times the sample size in order to use a binomial distribution