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Stat 260 final Exam Study Guide
Solutions
Correlation analysis - ANSWER✔✔-measures the strength of the relationship between two variables, x
and y
Residual - ANSWER✔✔-The difference between an observed y value and the estimated value (y-hat)
predicted by the regression equation. also known as the (random error, Ei)
Homoscedasticity - ANSWER✔✔-what is the assumption of equal standard deviations about the
regression line called?
Standard Error of estimate - ANSWER✔✔-the standard deviation describing the dispersion of data points
above and below the regression line (Sy*x)
Prediction Interval - ANSWER✔✔-for a given value of x, the estimation interval for an individual y
observation
Coefficient of Correlation - ANSWER✔✔-(r, with -1<r<1) is a number that indicates both the direction
and strength of the linear relationship between x and y
Coefficient of determination - ANSWER✔✔-r^2, its numerical value is the proportion of the variation in y
that is unexplained by the regression line, (y-hat=b+bx)
Sampling Distribution of the Mean - ANSWER✔✔-the probability distribution of the sample of means for
all possible samples of that particular size
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Standard Error of the Mean - ANSWER✔✔-the standard ddeviation of the sampling distibutiion of the
mean
Central limit theorem - ANSWER✔✔-Asserts that a distribution of sample means approaches a normal
curve as sample size increases
Scatterplot - ANSWER✔✔-the best graphical tool for examining the relationship between 2 quantitative
variables
Sample Correlation (r) - ANSWER✔✔-what is an "estimator" of population correlation (p)
Strong linear relation - ANSWER✔✔-r close to -1 or 1
weak linear relation - ANSWER✔✔-r close to 0
Causation - ANSWER✔✔-changes in X actually do cause changes in Y
confounding - ANSWER✔✔-the effect of X on Y is "hopelessly" mixed up with the effects of other
variables on Y
common response - ANSWER✔✔-both X and Y change as some unobserved third variable changes
mean squared error - ANSWER✔✔-MSE
SSE (sum of squared errors) - ANSWER✔✔-the sum of squared deviations from the regression
statistical inference - ANSWER✔✔-drawing conclusions about the population(parameter) based on a
sample (statistic)
Interval or ratio - ANSWER✔✔-simple linear regression requires that the scales of measurement be
expressed in?
Copyright ©Stuvia International BV 2010-2024 Page 2/9
Stat 260 final Exam Study Guide
Solutions
Correlation analysis - ANSWER✔✔-measures the strength of the relationship between two variables, x
and y
Residual - ANSWER✔✔-The difference between an observed y value and the estimated value (y-hat)
predicted by the regression equation. also known as the (random error, Ei)
Homoscedasticity - ANSWER✔✔-what is the assumption of equal standard deviations about the
regression line called?
Standard Error of estimate - ANSWER✔✔-the standard deviation describing the dispersion of data points
above and below the regression line (Sy*x)
Prediction Interval - ANSWER✔✔-for a given value of x, the estimation interval for an individual y
observation
Coefficient of Correlation - ANSWER✔✔-(r, with -1<r<1) is a number that indicates both the direction
and strength of the linear relationship between x and y
Coefficient of determination - ANSWER✔✔-r^2, its numerical value is the proportion of the variation in y
that is unexplained by the regression line, (y-hat=b+bx)
Sampling Distribution of the Mean - ANSWER✔✔-the probability distribution of the sample of means for
all possible samples of that particular size
Copyright ©Stuvia International BV 2010-2024 Page 1/9
, Copyright © KAYLIN 2024/2025 ACADEMIC YEAR. ALL RIGHTS RESERVED FIRST PUBLISH NOVEMBER, 2024
Standard Error of the Mean - ANSWER✔✔-the standard ddeviation of the sampling distibutiion of the
mean
Central limit theorem - ANSWER✔✔-Asserts that a distribution of sample means approaches a normal
curve as sample size increases
Scatterplot - ANSWER✔✔-the best graphical tool for examining the relationship between 2 quantitative
variables
Sample Correlation (r) - ANSWER✔✔-what is an "estimator" of population correlation (p)
Strong linear relation - ANSWER✔✔-r close to -1 or 1
weak linear relation - ANSWER✔✔-r close to 0
Causation - ANSWER✔✔-changes in X actually do cause changes in Y
confounding - ANSWER✔✔-the effect of X on Y is "hopelessly" mixed up with the effects of other
variables on Y
common response - ANSWER✔✔-both X and Y change as some unobserved third variable changes
mean squared error - ANSWER✔✔-MSE
SSE (sum of squared errors) - ANSWER✔✔-the sum of squared deviations from the regression
statistical inference - ANSWER✔✔-drawing conclusions about the population(parameter) based on a
sample (statistic)
Interval or ratio - ANSWER✔✔-simple linear regression requires that the scales of measurement be
expressed in?
Copyright ©Stuvia International BV 2010-2024 Page 2/9
