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.
positive
B.
inverse
C.
negative
D.
there is not enough information to estimate the nature of the correlation
Question #2
which statement is NOT true of Pearson’s Correlation Coefficient (r)?
A.
correlations provide statements of causation
B.
correlations can never exceed 1.0
C.
correlations can be negative
D.
correlations closer to 0.0 are considered to be weak, while correlations closer to 1.0 are considered to be strong.
Question #3
Choose the weakest correlation:
A.
(+0.12)
B.
-0.31
C.
(+0.58)
D.
-0.28
Question #4
Pearson’s Correlation Coefficient (r):
A.
presents the direction of the relationship
B.
presents the strength 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.
a positive relationship
B.
not enough information to answer question
C.
curvilienear relationship
D.
a negative relationship
Question #6
In a regresion equation a refers to:
A.
the amount of change in Y for each unit change in X
B.
the amount of change in X for each change in Y
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 ore the independent variable predicts the independent variable
B.
the worse the obtained data fit the regression line
C.
the less variance has been accounted for by the independent variable
D.
the better the obtained data fit the regression line (AKA line of best fit)
Question #8
The coefficient of determination explains:
A.
the proportion of the variance in Y that is explained by X
B.
the proporion of variance in Y that is attributed to error
C.
the proportion of variance in Y that is NOT explained by X
D.
the proportion of variance in X that is attributed to error
Question #9
In regression analysis:
A.
the independent variable is influenced by the dependent variable
B.
the independent variable must be categorical in nature
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 table has the same number of rows and columns
B.
the given table does not have the same number of row and columns
C.
there is a large sample
D.
the table is 2 x 2
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.
Pearson’s r
D.
Goodman’s and Kruskal’s Gamma
Question #12
When nominal data are presented in a 3 x 3 cross -tabulation, the correlation is computed usig the:
A.
Spearman’s r
B.
Contingency Coefficient
C.
Pearson’s r
D.
Phi coefficient
Question #13
To determine the relationshiop between rank-ordered or ordinal data, we compute:
A.
Spearman’s rank order correlation coefficient
B.
contingency coefficient
C.
Cramer’s V
D.
Pearson’s r
Question #14
The direction of the correlation is indicated by:
A.
both its size and sign (+ or -)
B.
its size
C.
neither its sign (+ or -) or size
D.
its sign (+ or -)
Question #15
In a regression equation, the slope accounts for:
A.
the point where the regression line crosses the Y axis when X = 0
B.
the points where the regression line crosses the X axis when Y = 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.
both nominal and interval
B.
interval level data
C.
nominal level data
D.
ordinal level data
Question #17
As measure association, the Phi coefficient can only be used
A.
for nominal data
B.
when random sampling has been used
C.
for tables that are 2 x 2
D.
all of the above
Question #18
A strong correlation between variable X and Y implies:
A.
High scores on X are associated with high scores on Y
B.
X is a good predictor of 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.
Its sign (+ or - )
B.
Both
C.
Neither
D.
its size
Question #20
Its r2 = .37, the coefficient of non-determination is equal to:
A.
0.86
B.
0.92
C.
0.14
D.
0.63
Question #21
To calculate the Phi coefficient we require:
A.
Ordinal data
B.
Ranked scores
C.
The chi-square value
D.
All of the above
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