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18 Cards in this Set

  • Front
  • Back
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
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.
A and B are independent if knowing one occurs tells you nothing about the other
Constant that describes the population
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