Statistical
Analysis Lesson
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QUESTION 1
From the histogram or ogive of the variable "Pay",
the percentage of the sample paid more than $40000 is:
92.97%
22.68%
7.03%
0.96%
0.7 points
QUESTION 2
Which of the following chart types would be best to
illustrate the frequency of distribution of the variable "Age"?
Pie
chart
Scatter
plot
Line
graph
Histogram
Bar
chart
0.65 points
QUESTION 3
Which of the following variables is an example of nominal
data:
Age
Pay
Experience
Tenure
Gender
0.65 points
QUESTION 4
The most appropriate measure of central tendency when you
have "outliers" or extreme values in your dataset is:
Median
Mean
and mode
Harmonic
Mean
Only
the mode
0.65 points
QUESTION 5
Which of the following is an appropriate measure of
variability for the variable Gender:
IQR
Range
25th
percentile
Variance
None of
the above
0.65 points
QUESTION 6
The skewness of the variable Experience is:
0.33
0.29
-0.22
-0.63
-3.33
0.65 points
QUESTION 7
The kurtosis of the variable Experience is:
-0.63
-0.09
-0.22
2.03
2.37
0.65 points
QUESTION 8
Using the mean and the standard deviation for the variable
AGE, approximately what value would lie three standard deviations to the right
of the mean and therefore be considered an "outlier"?
32
123
76
65
0.65 points
QUESTION 9
Based on the Empirical Rule, what proportion of a normally
distributed sample lies within two standard deviations of the mean?
89%
95.0%
3.8%
2.6%
0.65 points
QUESTION 10
For a population comprising 30% males, what is the
probabilility of drawing a random sample of 313 and getting more than 94 males?
Hint: use the binomial distribution.
4.9%
30.0%
46.7%
50.0%
53.3%
0.65 points
QUESTION 11
If the variable "Education" were uniformly
distributed over the range measured in the sample, the mean would be:
12
13
16
20
Cannot
be calculated
0.65 points
QUESTION 12
Assume that Pay follows a normal distribution with the
parameters measured by the sample. Using this information, what proportion of
the population earns less than $37500?
1.3%
3.0%
5.6%
97.0%
98.0%
0.65 points
QUESTION 13
Assume that Pay follows a normal distribution with the
parameters measured by the sample. Using this information, what proportion of
the population earns between $45000 and $55000?
20.9%
48.6%
52.4%
73.3%
Cannot
be calculated
0.65 points
QUESTION 14
The lower bound of the 90% confidence interval for the mean
of the variable "Pay" is:
$49632
$49878
$50004
$51432
$51678
0.65 points
QUESTION 15
The upper limit of the 95% confidence interval for the
proportion of males in the sample is:
23.4%
25.0%
25.8%
35.1%
36.7%
0.65 points
QUESTION 16
In order test whether the mean Experince is more than 15
years, the hypotheses should be set up as follows:
H¬¬¬0¬:
µ≥15 and HA: µ≤15
H¬¬¬0¬:
µ≠15 and HA: µ=15
H¬¬¬0¬:
µ=15 and HA: µ≠15
H¬¬¬0¬:
µ≤15 and HA: µ>15
H¬¬¬0¬:
µ≥15 and HA: µ<15
0.65 points
QUESTION 17
For the equivalent group of employees at Ellion, the mean
gross annual remuneration is $51500 with a standard deviation of $7000. At a
10% significance level, testing the hypothesis that the results from the
BizProsammmple are the same results in the following decision:
Reject H¬¬¬0
Reject HA
Accept H¬¬¬0
Do not
reject H¬¬¬0
Do not
reject HA
0.65 points
QUESTION 18
When testing the hypothess that the proportion of males in
the sample is 35% at a 5% significance level, the decision is:
Accept
the null hypothesis
Do not
reject the null hypothesis
Reject
the null hypothesis
Reject
the alternative hypothesis
Do not
reject the alternative hypothesis
0.65 points
QUESTION 19
The correlation between Education and Pay indicates that:
As
Education increases, Pay decreases
As
Education increases, Pay increases
As
Education decreases, Pay increases
Pay
causes Education
Education
causes Pay
0.65 points
QUESTION 20
At a 1% significance level:
Pay and
Tenure are correlated
Pay and
Experience are correlated
Pay and
Education are correlated
Education
and Tenure are correlated
None of
the above
0.65 points
QUESTION 21
The regression equation between Pay (dependent variable) and
Education (independent variable) accounts for:
81.9%
of the variance in Pay
81.4% of the variance in Pay
43.4% of the variance in Pay
18.9% of the variance in Pay
0.65 points
QUESTION 22
The regression equation between Pay (dependnet variable) and
Education (independent variable) may be written as follows"
Pay =
2786 + 206*Education
Pay =
27138 + 1753*Education
Pay =
206 + 27138*Pay
Pay =
206 + 2786*Education
Education
= 2713 + 1753*Pay
0.65 points
QUESTION 23
The regression equation between Pay (dependnet variable) and
Education (independent variable)
An
extra year of education results in an increase in Pay of $27138
An
extra year of education results in an increase in Pay of $2786
An
extra year of education results in an increase in Pay of $1753
An
extra year of education results in an increase in Pay of $206
This
cannot be determined from the regression equation
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