EXST 2201 EXAM 3 QUESTIONS AND ANSWERS WITH
COMPLETE SOLUTIONS VERIFIED
In Chapter 09, what characteristic of columns of data values is being measured?
(9.1.1)
The movement between two columns of data values.
What is needed to measure the movement between two columns of data values?
(9.1.2)
Two columns of dependent data values.
Are two columns of both the Height and Weight of individuals appropriate to
measure movement? (9.1.3)
Yes, because both height and weight come from one individual.
Select the two important points to remember when interpreting statistics of
movement. (9.1.4)
Always look at the data first.
Movement is not causation.
Where does a lurking variable lurk? (9.1.5)
Outside of the data values collected.
Why is a lurking variable important? (9.1.6)
Because it affects the statistical results without our knowledge.
What is movement between two columns of data values? (9.1.7)
How the value of one variable moves in relation to the value of the other variable.
,Select all choices that are the statistical methods used to measure variable
relationship. (9.1.8)
A scatterplot.
Linear correlation.
Linear regression.
What type of relationship between two variables can a scatterplot detect? (9.1.9)
Any type of relationship.
Please match each variable with where it is plotted in a scatterplot. (9.1.10)
- The response variable
- The predictor variable
Plotted on the x-axis. - The predictor variable
Plotted on the y-axis. - The response variable
In the thought concept of variable relationship, please match each variable with
when it changes. (9.1.11)
- The predictor variable
- The response variable
Changes before the response variable changes. - The predictor variable
Changes after the predictor variable changes. - The response variable
What type of relationship between two variables can linear correlation detect?
(9.1.12)
Only a linear relationship.
Can linear correlation measure a linear relationship, as well as just detect it?
(9.1.13)
, Yes, it can measure both the direction and the strength of the linear relationship.
What is the range of values for linear correlation measure? (9.1.14)
-1 to +1, inclusive ( [-1,+1] ).
What information does linear regression give that linear correlation does not
give? (9.1.15)
The magnitude of the effect of the linear relationship.
Conceptually, how is the information about a linear relationship summarized in
linear regression? (9.1.16)
By the line of best fit through the middle of the scatterplot.
What statistical method will this book use to calculate the equation of the line in
linear regression? (9.1.17)
The least-squares method of linear regression.
What is a scatterplot used for in the field of statistics? (9.2.1)
To visually see the pattern of the relationship between two variables.
Using the scatterplot below, match each point with its x,y coordinates. (9.2.2)
(3800, 32) -A
(4900, 12) -B
(5700, 44) -C
(6300, 38) -D
Select the two parts done when analyzing a scatterplot. (9.2.3)
Look at the overall pattern.
Look for any exceptions to the overall pattern.
Select the overall patterns looked for in analyzing a scatterplot. (9.2.4)
COMPLETE SOLUTIONS VERIFIED
In Chapter 09, what characteristic of columns of data values is being measured?
(9.1.1)
The movement between two columns of data values.
What is needed to measure the movement between two columns of data values?
(9.1.2)
Two columns of dependent data values.
Are two columns of both the Height and Weight of individuals appropriate to
measure movement? (9.1.3)
Yes, because both height and weight come from one individual.
Select the two important points to remember when interpreting statistics of
movement. (9.1.4)
Always look at the data first.
Movement is not causation.
Where does a lurking variable lurk? (9.1.5)
Outside of the data values collected.
Why is a lurking variable important? (9.1.6)
Because it affects the statistical results without our knowledge.
What is movement between two columns of data values? (9.1.7)
How the value of one variable moves in relation to the value of the other variable.
,Select all choices that are the statistical methods used to measure variable
relationship. (9.1.8)
A scatterplot.
Linear correlation.
Linear regression.
What type of relationship between two variables can a scatterplot detect? (9.1.9)
Any type of relationship.
Please match each variable with where it is plotted in a scatterplot. (9.1.10)
- The response variable
- The predictor variable
Plotted on the x-axis. - The predictor variable
Plotted on the y-axis. - The response variable
In the thought concept of variable relationship, please match each variable with
when it changes. (9.1.11)
- The predictor variable
- The response variable
Changes before the response variable changes. - The predictor variable
Changes after the predictor variable changes. - The response variable
What type of relationship between two variables can linear correlation detect?
(9.1.12)
Only a linear relationship.
Can linear correlation measure a linear relationship, as well as just detect it?
(9.1.13)
, Yes, it can measure both the direction and the strength of the linear relationship.
What is the range of values for linear correlation measure? (9.1.14)
-1 to +1, inclusive ( [-1,+1] ).
What information does linear regression give that linear correlation does not
give? (9.1.15)
The magnitude of the effect of the linear relationship.
Conceptually, how is the information about a linear relationship summarized in
linear regression? (9.1.16)
By the line of best fit through the middle of the scatterplot.
What statistical method will this book use to calculate the equation of the line in
linear regression? (9.1.17)
The least-squares method of linear regression.
What is a scatterplot used for in the field of statistics? (9.2.1)
To visually see the pattern of the relationship between two variables.
Using the scatterplot below, match each point with its x,y coordinates. (9.2.2)
(3800, 32) -A
(4900, 12) -B
(5700, 44) -C
(6300, 38) -D
Select the two parts done when analyzing a scatterplot. (9.2.3)
Look at the overall pattern.
Look for any exceptions to the overall pattern.
Select the overall patterns looked for in analyzing a scatterplot. (9.2.4)
