Statistics 001 - Elementary Statistics I for the Social Sciences » Spring 2020 » Exam 4
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Question #1
If we correlated people’s height and their shoe size, the correlation would probably be:
A.
negative
B.
inverse
C.
there is not enough information to estimate the nature of the correlation
D.
positive
Question #2
which statement is NOT true of Pearson’s Correlation Coefficient (r)?
A.
correlations closer to 0.0 are considered to be weak, while correlations closer to 1.0 are considered to be strong.
B.
correlations can be negative
C.
correlations can never exceed 1.0
D.
correlations provide statements of causation
Question #3
Choose the weakest correlation:
A.
-0.31
B.
-0.28
C.
(+0.58)
D.
(+0.12)
Question #4
Pearson’s Correlation Coefficient (r):
A.
presents the strength of the relationship
B.
presents the direction of the relationship
C.
varies from -1.0 to +1.0
D.
all of the above
Question #5
As years of educaiton increase, the likelihood of domestic violence decreases. This is an example of :
A.
curvilienear relationship
B.
a positive relationship
C.
a negative relationship
D.
not enough information to answer question
Question #6
In a regresion equation a refers to:
A.
the amount of change in X for each change in Y
B.
the amount of change in Y for each unit change in X
C.
the point where the regression line crosses the Y-axis when X=0
D.
the point where the regresssion line corsses the X-axis when Y=0
Question #7
The stronger the correlation:
A.
the less variance has been accounted for by the independent variable
B.
the better the obtained data fit the regression line (AKA line of best fit)
C.
the worse the obtained data fit the regression line
D.
the ore the independent variable predicts the independent variable
Question #8
The coefficient of determination explains:
A.
the proportion of variance in X that is attributed to error
B.
the proportion of the variance in Y that is explained by X
C.
the proportion of variance in Y that is NOT explained by X
D.
the proporion of variance in Y that is attributed to error
Question #9
In regression analysis:
A.
the independent variable must be categorical in nature
B.
the independent variable is influenced by the dependent variable
C.
the variables being investigated must be correlated
D.
one variable is believed to be influenced by the other
Question #10
Cramer’s V is preferable to the Contingency Coefficient when:
A.
the given table does not have the same number of row and columns
B.
the table has the same number of rows and columns
C.
the table is 2 x 2
D.
there is a large sample
Question #11
When ordinal data measurement produces a large number of tied ranks, we should use:
A.
Cramer’s V
B.
Spearman’s r
C.
Goodman’s and Kruskal’s Gamma
D.
Pearson’s r
Question #12
When nominal data are presented in a 3 x 3 cross -tabulation, the correlation is computed usig the:
A.
Contingency Coefficient
B.
Pearson’s r
C.
Phi coefficient
D.
Spearman’s r
Question #13
To determine the relationshiop between rank-ordered or ordinal data, we compute:
A.
Spearman’s rank order correlation coefficient
B.
Pearson’s r
C.
Cramer’s V
D.
contingency coefficient
Question #14
The direction of the correlation is indicated by:
A.
its sign (+ or -)
B.
neither its sign (+ or -) or size
C.
both its size and sign (+ or -)
D.
its size
Question #15
In a regression equation, the slope accounts for:
A.
the points where the regression line crosses the X axis when Y = 0
B.
the point where the regression line crosses the Y axis when X = 0
C.
the amount of change in X for each unit change in Y
D.
the amount of change in Y for each unit change in X
Question #16
Which of the following is a requirement when computing Spearman’s Correlation Coefficient?
A.
interval level data
B.
both nominal and interval
C.
nominal level data
D.
ordinal level data
Question #17
As measure association, the Phi coefficient can only be used
A.
for tables that are 2 x 2
B.
when random sampling has been used
C.
for nominal data
D.
all of the above
Question #18
A strong correlation between variable X and Y implies:
A.
X is a good predictor of Y
B.
High scores on X are associated with high scores on Y
C.
low scores on X are associated with low scores on Y
D.
X is NOT a good predictor of Y
Question #19
The strengh of the correlation is indicated by:
A.
Neither
B.
Both
C.
its size
D.
Its sign (+ or - )
Question #20
Its r2 = .37, the coefficient of non-determination is equal to:
A.
0.86
B.
0.14
C.
0.92
D.
0.63
Question #21
To calculate the Phi coefficient we require:
A.
Ranked scores
B.
Ordinal data
C.
The chi-square value
D.
All of the above
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