C784 MODULE 6 CORRELATION & REGRESSION. EXAM REVISION
QUESTIONS AND CORRECT ANSWERS (ALREADY GRADED A+)
(LATEST 2025 UPDATE)
lurking variable - Answer -A variable that is not included in an analysis but that is related to two
(or
more) other associated variables which were analyzed.
simple linear regression - Answer -the prediction of one response variable's value from one
explanatory
variable's value
Simpson's Paradox - Answer -A counterintuitive situation in which a trend in different groups of
data
disappears or reverses when the groups are combined.
degree - Answer -The largest exponent in a mathematical expression or equation.
causation - Answer -A relationship of cause and effect between two or more variables.
linear interpolation - Answer -Estimation using the linear regression equation is between known
data
points.
association - Answer -A pattern or relationship between two variables.
coordinate plane - Answer -A tool for graphing consisting of a horizontal x-axis and a vertical y-
axis.
regression equation - Answer -An equation used to model the relationship between two
quantitative
dependent and independent variables.
,scatterplot - Answer -A graph that uses dots on a coordinate plane to show the relationship
between
variables.
Regression Analysis - Answer -a statistical tool that quantifies the relationship betwn a response
variable
and one or more explanatory variables
least squares - Answer -A technique for finding the regression line.
slope-intercept form - Answer -A common format for the equation of a line: y = mx + b, where m
is the
slope and b is the y-intercept.
regression line - Answer -The line of best fit to show the relationship between variables, the one
that
minimizes distance from each data point to the line.
A linear regression equation takes the following form:
y = mx^2 + b. True or False? - Answer -false.
This is not the form that a linear regression equation takes.
Linear regression is always of degree 1, so the exponent of 2 associated with the x makes this a
nonlinear equation.
A linear regression "best-fit-line" can be estimated using least squares. True or False? - Answer -
true.
Least squares estimation is the most common technique used to estimate the best-fit-line in linear
regression.
Linear extrapolation is always a reliable method of prediction. True or False? - Answer -false.
Extrapolation assumes that the linear pattern of the data will continue outside of the range of data
, points. This may not always be the case and therefore may not always be a reliable method of
prediction.
Linear interpolation is a technique used to make a prediction that falls between known data
points. True
or False? - Answer -true.
Linear interpolation is a technique used to make a prediction that falls between known data
points,
using the linear regression equation.
Least squares estimation is a technique for predicting future data values. True or False? - Answer
-false.
Least squares estimation is a technique used to estimate the best-fit-line in linear regression.
EXTRAPOLATE - Answer -Using information from a data set to make predictions about data
outside of the
original set.
POPULATION - Answer -An entire pool from which a sample is drawn.
SAMPLE SIZE - Answer -Statistics: the number of individuals measured or observed in a study.
Probability: number of possible outcomes in a trial or experiment.
Extrapolation is always inappropriate. True or False? - Answer -false.
There are applications of extrapolation, and times in which it is necessary. Be mindful of the
situation
and try to avoid inappropriate extrapolation by considering the context.
Which of the following statements is most appropriate with regards to representative samples?
a. The risk of non-representative sample decreases as sample size increases.
b. The risk of non-representative sample size decreases as sample size decreases.
QUESTIONS AND CORRECT ANSWERS (ALREADY GRADED A+)
(LATEST 2025 UPDATE)
lurking variable - Answer -A variable that is not included in an analysis but that is related to two
(or
more) other associated variables which were analyzed.
simple linear regression - Answer -the prediction of one response variable's value from one
explanatory
variable's value
Simpson's Paradox - Answer -A counterintuitive situation in which a trend in different groups of
data
disappears or reverses when the groups are combined.
degree - Answer -The largest exponent in a mathematical expression or equation.
causation - Answer -A relationship of cause and effect between two or more variables.
linear interpolation - Answer -Estimation using the linear regression equation is between known
data
points.
association - Answer -A pattern or relationship between two variables.
coordinate plane - Answer -A tool for graphing consisting of a horizontal x-axis and a vertical y-
axis.
regression equation - Answer -An equation used to model the relationship between two
quantitative
dependent and independent variables.
,scatterplot - Answer -A graph that uses dots on a coordinate plane to show the relationship
between
variables.
Regression Analysis - Answer -a statistical tool that quantifies the relationship betwn a response
variable
and one or more explanatory variables
least squares - Answer -A technique for finding the regression line.
slope-intercept form - Answer -A common format for the equation of a line: y = mx + b, where m
is the
slope and b is the y-intercept.
regression line - Answer -The line of best fit to show the relationship between variables, the one
that
minimizes distance from each data point to the line.
A linear regression equation takes the following form:
y = mx^2 + b. True or False? - Answer -false.
This is not the form that a linear regression equation takes.
Linear regression is always of degree 1, so the exponent of 2 associated with the x makes this a
nonlinear equation.
A linear regression "best-fit-line" can be estimated using least squares. True or False? - Answer -
true.
Least squares estimation is the most common technique used to estimate the best-fit-line in linear
regression.
Linear extrapolation is always a reliable method of prediction. True or False? - Answer -false.
Extrapolation assumes that the linear pattern of the data will continue outside of the range of data
, points. This may not always be the case and therefore may not always be a reliable method of
prediction.
Linear interpolation is a technique used to make a prediction that falls between known data
points. True
or False? - Answer -true.
Linear interpolation is a technique used to make a prediction that falls between known data
points,
using the linear regression equation.
Least squares estimation is a technique for predicting future data values. True or False? - Answer
-false.
Least squares estimation is a technique used to estimate the best-fit-line in linear regression.
EXTRAPOLATE - Answer -Using information from a data set to make predictions about data
outside of the
original set.
POPULATION - Answer -An entire pool from which a sample is drawn.
SAMPLE SIZE - Answer -Statistics: the number of individuals measured or observed in a study.
Probability: number of possible outcomes in a trial or experiment.
Extrapolation is always inappropriate. True or False? - Answer -false.
There are applications of extrapolation, and times in which it is necessary. Be mindful of the
situation
and try to avoid inappropriate extrapolation by considering the context.
Which of the following statements is most appropriate with regards to representative samples?
a. The risk of non-representative sample decreases as sample size increases.
b. The risk of non-representative sample size decreases as sample size decreases.
