## Transcribed Text

Question 1 of 4
1.0 Points
You have been given sample data from two offices and told that the 95% confidence interval for the difference of mean in overtime hours per
year is -.01 to 100. What can you say about the difference in average overtime hours for each office?
A. Overtime hours are statistically significant at alpha= 05
B. Overtime hours are not statistically significant at a 95% confidence level.
C. Overtime hours are practically significant.
D. We can't tell from the data.
Question 2 of 4
1.0 Points
What if told you in Q1 above that the sample sizes were n=20 and n=30 for each office, what would you say then?
A.A sample size of 30 is the minimum sample size to make the law of large numbers work, so we cannot draw conclusions from this data
B. Use a t-score for the smaller sample and z-score for the larger one.
C. If the sample sizes were increased, we would likely see statistically significant difference at the 95% confidence level.
D and C
B and C
Question 3 of 4
1.0 Points
You have conducted a pilot study of new initiative to improve employee morale, using experimental design on samples of employees, and
you have found that ina regression equation morale has improved by points out of 10, with a p-value of .07.
What can you say about your pilot study?
B.
My regression coefficient does not meet standards for statistical significance, and on that basis cannot draw firm conclusions about my
innovation.
c. The confidence interval for morale likely includes 0.
D.A and C.
E. All of the above.
Reset Selection
Question 4 of 4
1.0 Points
For the examples below comparing Boys' and Girls Mean Test Scores, match the example to the proper qualitative description. (Pay
attention to sample size, difference in scores, and measures of significance). T-scores are given throughout for comparability
A. We're sure that there is no difference of magnitude large enough to matter.
B. An important difference that's really there.
C. Could be large, important difference, but we have no idea. Not enough data to tell.
D. Lots of data make small, unimportant difference statistically significant.
1.
Example A
Sample
10,000
Size
Overall
200
Mean
Std. Dev.
25
Girls'
Mean
175
Score
select
Boys'
Mean
225
Score
Difference
50
in Score
Standard
=2xSD/sqrt(10,000)
Error of
=2x25/sqrt(10,000)
the
=.5
Difference
t-score
= 100
and
<< .0001
p-value
Example B
Sample
10.000
Size
Overall
200
Mean
Std. Dev.
25
Girls'
Mean
199
Score
Boys'
select
Mean
201
Score
Difference
in Score
Standard
=2xSD/sqrt(10,000)
Error of
2225/sqrt(10,000)
the
-.5
Difference
t-score
=4
and
p<.001
p-value
3.
Example C
Sample Size 9
Overall Mean 200
Std. Dev.
100
Girls' Mean
175
Score
select
Boys' Mean
225
Score
Difference in
50
Score
Standard
=2xSD/sqrt(9)
Error the
=2x100/sgrt(9)
Difference
-66.6
t-score and
=.75
p-value
p>.40
4.
Example D
Sample
1,000
Size
Overall
200
Mean
Std. Dev.
25
Girls'
Mean
199
Score
select
Boys'
Mean
201
Score
Difference
2
in Score
Standard
=2xSD/sqrt(1,000
Error
-2x25/sqrt(1,000
the
=1.58
Difference
t-score
1.26
land
p-value

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