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Chapter 3: Describing Relationships Flashcards | StudBud
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Chapter 3: Describing Relationships
Chapter 3: Describing Relationships
26 terms
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#RayBanMathMan
Flashcards
26 cards
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Questions
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Answers
1
Match the following scatterplot to the r value below that best describes it
-0.3
-0.99
-0.7
0
2
Match the following scatterplot to the r value below that best describes it
-0.3
-0.7
0
-0.99
3
Match the following scatterplot to the r value below that best describes it
0
-0.99
-0.7
-0.3
4
If r= -1, then we can conclude that there is a perfect relationship between X and Y.
False
True
5
Which of the following is incorrect in regards to correlations?
Correlation does not imply causation
Correlation is not a complete summary of two-variable data
Like the mean & standard deviation, correlation is resistant
Correlation requires that both variables be quantitative
6
The least squares regression line minimizes the sum of the
Absolute deviations between actual and predicted Y values
Differences between actual and predicted Y values
Differences between actual and predicted x values
Squared differences between actual and predicted Y values
7
It is found that grades in math and hours of time spent completing homework have an association
Time spent studying and completing homework
Homework
Connection between the variables is not clear
Grade in mathematics
8
Suppose a study finds that the correlation relating family income to SAT scores is r=1.
Poverty causes low SAT scores
Wealth causes high SAT scores
No conclusions can be made
There is a strong association between income and SAT scores
9
Match the following scatterplot to the r value below that best describes it
0
-0.7
-0.3
-0.99
10
Which of the following statements, concerning least squares regression lines (LSRL), is true?
All of the above
A plot of the residuals is useful for assessing fit of LSRL
residual= observed y- predicted y
The sum of the residuals is always 0
11
The correlation coefficient is
A positive number that measure only the strength
Always equal to the slop of the regression line
Never equal to 0
Number between -1 and +1 that measures strength & direction
12
The strength of the relationship between two quantitative variables can be measure by the:
Coefficient of correlation
Slope of the regression equation
Y intercept of the regression equation
Coefficient of determination
13
Which of the following statements is true?
Correlation changes when the x and y variables are reversed
Strong correlation refers to a cause and effect relationship
Values of r near 0 indicate a strong linear relationship
The correlation can be strongly affected by outliers
14
Match the following scatterplot to the r value below that best describes it
-0.99
-0.7
0
-0.3
15
Match the following scatterplot to the r value below that best describes it
-0.3
-0.99
0
-0.7
16
The correlation coefficient may assume any value between
0 and 1
0 and 10
-1 and 1
-1 and 0
17
Which of the following best describes the correlation between two variables if r= 0.978?
Negative and weak
Positive and weak
Negative and strong
Positive and strong
18
Match the following scatterplot to the r value below that best describes it
-0.7
-0.3
-0.99
0
19
Match the following scatterplot to the r value below that best describes it
-0.99
-0.3
0
-0.7
20
Match the following scatterplot to the r value below that best describes it
0
-0.3
-0.7
-0.99
21
Match the following scatterplot to the r value below that best describes it
-0.3
-0.99
-0.7
0
22
A study is conducted to determine if college academic results can be predicted based on HS GPA
The college
Academic performance of the first year student
Number of credits the student is taking
Grade point average (GPA)
23
Match the following scatterplot to the r value below that best describes it
-0.3
-0.99
0
-0.7
24
Match the following scatterplot to the r value below that best describes it
-0.3
-0.99
0
-0.7
25
The least squares regression line for average tree height based on trunk diameter: Y^=-3.6+4x,
20.1
7.4
24.4
31.6
26
Which of the following statements about correlation r are incorrect?
It's not affected by which variable is called x or y
It is not affected by extreme values
Correlation r is just a number
It is not affected by changes in measurement units
