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.
positive
C.
there is not enough information to estimate the nature of the correlation
D.
inverse
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.
-0.31
B.
(+0.12)
C.
-0.28
D.
(+0.58)
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.
not enough information to answer question
B.
a positive relationship
C.
a negative relationship
D.
curvilienear relationship
Question #6
In a regresion equation a refers to:
A.
the amount of change in X for each change in Y
B.
the point where the regresssion line corsses the X-axis when Y=0
C.
the point where the regression line crosses the Y-axis when X=0
D.
the amount of change in Y for each unit change in X
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 ore the independent variable predicts the independent variable
D.
the worse the obtained data fit the regression line
Question #8
The coefficient of determination explains:
A.
the proportion of the variance in Y that is explained by X
B.
the proportion of variance in X that is attributed to error
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 is influenced by the dependent variable
B.
the variables being investigated must be correlated
C.
the independent variable must be categorical in nature
D.
one variable is believed to be influenced by the other
Question #10
Cramer’s V is preferable to the Contingency Coefficient when:
A.
there is a large sample
B.
the table is 2 x 2
C.
the table has the same number of rows and columns
D.
the given table does not have the same number of row and columns
Question #11
When ordinal data measurement produces a large number of tied ranks, we should use:
A.
Spearman’s r
B.
Cramer’s V
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.
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.
Pearson’s r
D.
Cramer’s V
Question #14
The direction of the correlation is indicated by:
A.
its size
B.
its sign (+ or -)
C.
both its size and sign (+ or -)
D.
neither its sign (+ or -) or size
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.
interval level data
B.
nominal level data
C.
both nominal and interval
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.
low scores on X are associated with low scores on Y
B.
X is NOT a good predictor of Y
C.
X is a good predictor of Y
D.
High scores on X are associated with high scores on Y
Question #19
The strengh of the correlation is indicated by:
A.
Its sign (+ or - )
B.
its size
C.
Neither
D.
Both
Question #20
Its r2 = .37, the coefficient of non-determination is equal to:
A.
0.63
B.
0.86
C.
0.14
D.
0.92
Question #21
To calculate the Phi coefficient we require:
A.
The chi-square value
B.
Ordinal data
C.
Ranked scores
D.
All of the above
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