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MIDTERM STUDY QUESTIONS
Q1.
The table shown below contains information technology (IT) investment as a percentage
of total investment for eight countries during the 1990s. It also contains the average
annual percentage change in employment during the 1990s. Explain how these data shed
light on the question of whether IT investment creates or costs jobs.
(Hint: Make use of
relevant graphical tools)
To analyze this we plot each country’s annual percentage change in employment during the 1990s
on the vertical axis and the corresponding information technology (IT) investment as a percentage
of total investment for eight countries on the horizontal axis. In order to sow the relationship, I
created a scatter plot graph by the help of stat tools function of excel. As the points tend to move
up and to the right, and as the correlation between these two variables is 0.930, this implies a
reasonably strong positive linear relationship between IT investment and the jobs. Briefly we can
say that IT investment creates jobs.
Q2.
1
Country
% IT
% Change
Netherlands
2.5%
1.6%
Italy
4.1%
2.2%
Germany
4.5%
2.0%
France
5.5%
1.8%
Canada
8.3%
2.7%
Japan
8.3%
2.7%
Britain
8.3%
3.3%
U.S.
12.4%
3.7%
for eight countries during the 1990s

The percentage of the US population without health insurance coverage for samples from the 50
states and District of Columbia for both 2003 and 2004 produced the following tables of
summary measures and correlations.
Summary Measures Table:
Percentage in 2003
Percentage in 2004
Count
51.000
51.000
Mean
14.455
14.855
Median
13.700
14.200
Standard deviation
3.724
4.098
Minimum
9.100
8.000
Maximum
24.900
26.300
First quartile
11.600
12.200
Third quartile
16.800
16.500
Skewness
0.910
0.699
Table of Correlations:
Percent 2003
a. Describe the distribution of
state percentages of Americans
without health insurance coverage in 2004.
Be sure to employ both measures of central
location and dispersion in developing your characterization of this sample. ( 5 pts)
The variance is essentially the average of the squared deviations from the mean. A more intuitive
measure is the standard deviation, defined as the square root of the variance. The distribution of
state percentages of Americans without health insurance coverage in 2004 can be summarized as
below;
As the mean of the population is 14.855;
If the data was approximately symmetric, then the 1
st
,2
nd
and the 3
rd
quartiles had to include these
below values;
Approximately 68% of the observations are within 1 standard deviation of the mean, that is,
within the interval
͞
X±S which turns this range (10.757,18.953)
Approximately 95% of the observations are within 2 standard deviation of the mean, that is,
within the interval
͞
X±2S which turns this range (6.659,23.051)
Approximately 99.7% of the observations are within 3 standard deviation of the mean, that is,
within the interval
͞
X±3S which turns this range (2.561,27.149)
As the distribution is skewed, we can say that in 2004, the state percentages of Americans

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