EXST 2201 EXAM 3 QUESTIONS AND ANSWERS WITH
COMPLETE SOLUTIONS GRADED A++
(9.1)In Chapter 09, what characteristic of columns of data values is being
measured?
The means of two columns of data values.
The variances of two columns of data values.
The difference between two columns of data values.
The movement between two columns of data values.
The movement between two columns of data values.
(9.1)What is needed to measure the movement between two columns of data
values?
Two columns of independent data values.
Three columns of dependent data values.
Two columns of dependent data values.
Two columns of data values in the long view.
Two columns of dependent data values.
(9.1)Are two columns of both the Height and Weight of individuals appropriate to
measure movement?
Yes, because both height and weight come from one individual.
Yes, because both height and weight can be put into the long view.
,No, because two columns of independent data values are needed.
No, because Height and Weight do not have the same units of measurement.
Yes, because both height and weight come from one individual.
(9.1)Select the two important points to remember when interpreting statistics of
movement.
Select Answer(s)
Always look at the data first.
Hand calculate to confirm the statistics.
Movement is not causation.
Statistics are always correct.
Always look at the data first.
Movement is not causation.
(9.1)Where does a lurking variable lurk?
Outside of the data values collected.
In a dark alleyway.
Between two columns of data values.
In the missing data of a data set.
Outside of the data values collected.
(9.1)Why is a lurking variable important?
Because a good statistical method should include the lurking variable.
, Because when it exists, it is important.
Because it affects the statistical results without our knowledge.
Because it is the most important variable in the study.
Because it affects the statistical results without our knowledge.
(9.1)What is movement between two columns of data values?
How the mean of one variable moves in relation to the mean of the other variable.
How the value of one variable moves in relation to the value of the other variable.
How the variances of the two variables adjust toward each other.
How the values of the two variables move along the real number line.
How the value of one variable moves in relation to the value of the other variable.
(9.1)Select all choices that are the statistical methods used to measure variable
relationship.
Select Answer(s)
Linear regression.
A stem-and-leaf plot.
A scatterplot.
Linear hypothesis test.
Linear correlation.
A scatterplot.
Linear correlation.
Linear regression.
(9.1)What type of relationship between two variables can a scatterplot detect?
Only a curvilinear relationship.
COMPLETE SOLUTIONS GRADED A++
(9.1)In Chapter 09, what characteristic of columns of data values is being
measured?
The means of two columns of data values.
The variances of two columns of data values.
The difference between two columns of data values.
The movement between two columns of data values.
The movement between two columns of data values.
(9.1)What is needed to measure the movement between two columns of data
values?
Two columns of independent data values.
Three columns of dependent data values.
Two columns of dependent data values.
Two columns of data values in the long view.
Two columns of dependent data values.
(9.1)Are two columns of both the Height and Weight of individuals appropriate to
measure movement?
Yes, because both height and weight come from one individual.
Yes, because both height and weight can be put into the long view.
,No, because two columns of independent data values are needed.
No, because Height and Weight do not have the same units of measurement.
Yes, because both height and weight come from one individual.
(9.1)Select the two important points to remember when interpreting statistics of
movement.
Select Answer(s)
Always look at the data first.
Hand calculate to confirm the statistics.
Movement is not causation.
Statistics are always correct.
Always look at the data first.
Movement is not causation.
(9.1)Where does a lurking variable lurk?
Outside of the data values collected.
In a dark alleyway.
Between two columns of data values.
In the missing data of a data set.
Outside of the data values collected.
(9.1)Why is a lurking variable important?
Because a good statistical method should include the lurking variable.
, Because when it exists, it is important.
Because it affects the statistical results without our knowledge.
Because it is the most important variable in the study.
Because it affects the statistical results without our knowledge.
(9.1)What is movement between two columns of data values?
How the mean of one variable moves in relation to the mean of the other variable.
How the value of one variable moves in relation to the value of the other variable.
How the variances of the two variables adjust toward each other.
How the values of the two variables move along the real number line.
How the value of one variable moves in relation to the value of the other variable.
(9.1)Select all choices that are the statistical methods used to measure variable
relationship.
Select Answer(s)
Linear regression.
A stem-and-leaf plot.
A scatterplot.
Linear hypothesis test.
Linear correlation.
A scatterplot.
Linear correlation.
Linear regression.
(9.1)What type of relationship between two variables can a scatterplot detect?
Only a curvilinear relationship.
