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EXCEL ASSIGNMENT #1
We assume that all students have had an introduction to Excel. The instructions given below
are an outline of the steps you need to take in order to complete your assignment. They
should be regarded as a guide and not a detailed map of the procedure. Further help on
using Excel is available on for download with the Excel assignment from our course web site
and by clicking on the Excel Help menu.
Please be sure to read the instructions listed below before you begin the computer exercise.
By doing so, you will have a clearer understanding of the purpose of the exercise and how you will
conduct the analysis. This could help reduce the amount of time you spend in the computer lab. on
this assignment.
Case Description
Corporations with international operations need to assess the risks associated with setting up and
maintaining operations in different regions of the world. Consideration of the risks include
considering such issues as political and economic stability. One indicator of the healthcare and
quality of life in a country or region that is considered correlated with the risk and stability in the
region is the child mortality rate. As a result, the healthcare and quality of care as measured by the
child mortality rate in a region can impact the type and amount of investment in a region and
countries within a region. The child mortality rate is the number of children 5 and under that die
per thousand people in the population. The Inter-agency Group for Child Mortality Estimation
(IGME) was obtained from www.childmortality.org. In 2008 the US rate was 7.6 deaths per
thousand and in North America (US and Canada) the rate was 6.65 with a standard deviation of
0.68. The Excel file for this assignment has labels for the year, country name, and continent group.
NAME OF FIELD
DESCRIPTION
Country
Name of the countries
Continent / Region
Countries were categories based on region
into 8 continents. The coding scheme was 1=
South-East Asia, 2 = South Asia, 3 = Western
Europe, 4 = Eastern Europe, 5 = Africa, 6 =
South America and Islands, 7 = Oceania with
Australia and New Zealand, 8 = Middle East,
9 = North America
CMR1998
child mortality rate for 1998
CMR2008
child mortality rate for 2008
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Use the provided random sample of observations to test the hypotheses that
(i) the mean child mortality rate for countries in Africa is more than the mean Child
mortality rate for countries in South Asia. ( = .05),
(ii) the mean child mortality rate for countries in Eastern Europe is more than the mean
Child mortality rate for countries in the Middle East. ( = .01),
(iii) the mean child mortality rate for countries in South East Asia is more than the mean
Child mortality rate for countries in Western Europe. ( = .05) by 10 per thousand.
1. You will need to have the data file for this assignment (Assgt#1.xls) copied onto a disk or flash
drive. You can do this in a variety of ways. Perhaps the easiest way is to simply copy all the
relevant files for the Excel assignments. These files reside on the course web site on the Excel files
page that you can find by clicking on the Excel files link near the top of the page.
2. Click on the file to download and allow about a half minute for the downloading to be
completed.
Beginning with the standard screen in the COBA computer labs:
3. Click on Spreadsheets & Database, then on Microsoft Excel 2007.
4. Click on File Open, click on Look In, then on the down arrow. Choose the address where the
data file resides and select Assgt#1.xls
5. Highlight the all data and Sort by Continent (region). The data is shown below before and after
the sort
Original data
Country
Afghanistan
Algeria
Angola
Argentina
Australia
Bahrain
Belarus
Region CMR1998
CMR2008
2
257
257
5
49.4
37
5
213.9
158
6
23.6
16.2
7
6.6
5.7
8
14.1
10.2
4
19.8
13.4
Country
Brunei
Indonesia
Korea, Dem. Rep.
Region CMR1998 CMR2008
1
8.92
8.8
1
58.8
31.2
1
55
55
Sorted data
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6. Copy the net child mortality rates for the sample of countries in Africa (Continent = 5) and paste
these values into a new column, beginning at the second row. Put a title (label) at the top of this
new column to indicate what the values represent (e.g., Africa-CMR2008). Next, copy the net
income for child mortality rates for the sample of countries in the South Asia (Continent = 2) and
paste these values in the column adjacent to the first new column. Put a title (label) at the top of the
newest column to indicate what these values represent (e.g., SoAsia-CMR2008).Please note that in
these two new columns you should have numbers representing child mortality rates per 1000 and
NOT the 5s or 2s! The table below shows what the first lines in your two new columns should
resemble.
Africa2008
37
158
So-Asia2008
257
84
7. Select the Data tab then Click on Data Analysis (In Office 2003 - Click on Tools then Data
Analysis), then on descriptive statistics and check the ‘summary statistics’ box. Examine that data
and consider its meaning.
Africa2008
Mean
Standard Error
Median
Mode
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Sum
Count
So-Asia2008
137.175
2748.53671
Mean
105.0175
Sample Variance
11411.13
20 Count
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8. Once the descriptive statistics are examined, repeat the steps to get to Excel Data Analysis
macros and select the t-test: Two-Sample Assuming Unequal Variances. Then set the cursor in the
Variable 1 box, and then highlight the column with Africa-CMR2008 data. Repeat with the
Variable 2 box and the SoAsia-CMR2008 data.
9. Click in the labels box to put a check mark, and take the default .05 significance level.
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10. Enter 0 (the number zero) in the box for hypothesized mean difference.
11. Click on the Output Range radio button then set the cursor in the box beside it and choose
any convenient 13 row x 4 column space in your current Excel spreadsheet. Click on O.K.
12. Excel will then complete the independent two-samples t-test and place the output in the space
that you named. Expand the column widths if necessary to reveal all of the output without
truncation. Your output might resemble the truncated version of the output shown below:
t-Test: Two-Sample Assuming Unequal Variances
Africa2008 So-Asia2008
Mean
137.175
105.0175
Variance
2748.53671 11411.12789
Observations
20
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Hypothesized Mean
Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail
13. Repeat steps 6 and 8-12 but with CMR data for countries in the Eastern European Region (4)
and the Middle East (8). In Step 7 you will need to select the t-test for "Equal Variances".
Make a separate pair of new columns with an appropriate title at the top of each column and be sure
to change the  level to .01 but use the same hypothesized mean difference of 0. Below is a
truncated illustration of the test output.
t-Test: Two-Sample Assuming Equal Variances
Eastern
European
Mean
15.8375
Variance
119.382679
Observations
8
Pooled Variance
Hypothesized Mean
Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail
Middle East
15.71428571
80.18809524
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14. Repeat steps 6 and 8-12 but with CMR data for countries in the Western European Region and
the South East Asia. In Step 7 you will need to select the t-test for "Unequal Variances". Make
a separate pair of new columns with an appropriate title at the top of each column and be sure to
change the  level to .05 and the hypothesized mean difference to 10. Below is a truncated
illustration of how the test output might look.
t-Test: Two-Sample Assuming Unequal Variances
Mean
Variance
Observations
Hypothesized Mean
Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail
So E Asia
35.95
Western
Europe
5.775
1432.551
6
42.26568
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15. Print out the data and output for each of your three t-tests. You might want to answer the
questions by typing on the Excel Spreadsheet before printing. Alternatively you can copy and
paste the output in the Excel window into a word processor (e.g., Microsoft Word or WordPerfect)
and type your answers there. Whatever method you choose, you should understand the link
between each answer and the relevant Excel output to which it refers.
For this assignment you should print the following on your spreadsheet.
Below each of the three t-test outputs, the null and alternative hypotheses, a decision, giving the
reason, and a conclusion based on the output. For example
Null Hypothesis, Ho: the mean child mortality rate for countries in Africa is
the mean child
mortality rate for countries in South Asia.
Alternative Hypothesis, Ha: the mean child mortality rate for countries in Africa is
the mean
child mortality rate for countries in South Asia.
Decision: Fail to reject (or reject - as your results determine) Ho because the p-value (xxxx)
associated with the test statistic is ____ than the significance level (0.05).
Conclusion: there is evidence (or insufficient evidence - as your results determine) that the mean
child mortality rate for countries in Africa is ____ the mean child mortality rate for countries in
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South Asia.
The Excel assignments are each graded via a short Excel Quiz in HLS Web Test that is open for
about 48 hours as listed in the syllabus and in your HLS progress report. A sample of the type of
quiz you will be given is provided at the end of these instructions. You are expected to use your
output and written answers to complete the quiz. You are not required to turn in the output.
We also want you to work in groups of 3-5 to discuss each of the following questions.
Experiential Exercise
As you work this assignment think about the following questions. Then form a team of 3 to 5 and
discuss each of the following. You can engage in this discussion by meeting or your group can use
a Wiki to engage in an online discussion. Instructions for setting up a Wiki are provided on the
excel assignment page of our course web site.
1. What wording tells you the alternative and null hypothesis?
2. What wording tells you the type of statistical test to perform? For example, is a z or t
statistic appropriate?
3. What wording tells you that this is a one or two tail hypothesis test?
4. What were the steps you used to obtain the calculated value of the test statistic?
5. What were the steps you used to obtain the critical value of the test statistic?
6. How do you use the calculated and critical value to make a statistical decision about this
test?
7. How do you obtain the p value for the test statistic?
8. How do you use the p value and the level of significance to make a statistical decision about
this test?
9. How does the result of your test relate to the statistical significance of your findings?
10. What managerial implications can you conclude from the results of your test?
Multicultural Topic Related Exercise
As you work this assignment think about the following questions. Then form a team of 3 to 5 and
discuss each of the following. You engage in this discussion by meeting or your group can use a
Wiki to engage in an online discussion. Instructions for setting up a Wiki are provided on the excel
assignment page of our course web site.
1. State any pre-conceived opinion you held about how the US data might relate to the data of
other countries. Discuss how the statistical analysis of the sample data supported or refuted
your prior opinion.
2. State in your own words the implications of the results of the statistical tests that you were
asked to conduct in the exercise.
3. How would you have conducted a formal test to see if your preconceived opinion was
correct or not?
4. What policies might be impacted by the statistical results and examination of the
descriptive statistics in this assignment?
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WEBTEST like sample Quiz: The questions below are much like the quiz you will have in
WEBTEST. If you can answer these, you should have no difficulty with those that will be asked.
However, these questions are not the exact questions that you will have to answer.
The correct answers to the sample questions are highlighted.
1. What is the critical value for the t-test to compare the mean child mortality rate for countries in
Africa with the mean child mortality rate for countries in South Asia?
A. 2.35
B. 0.05
C. 0
D. 3.18
E. 0.588
2. What is the critical value for the t-test to determine if the mean child mortality rate for countries
in Eastern Europe is more than the mean Child mortality rate for countries in the Middle East?
A. 2.65
B. 0.05
C. 3.01
D. 0
E. 0.024
3. The hypothesized mean difference to conduct the test to determine if the mean child mortality
rate for countries in Eastern Europe is more than the mean Child mortality rate for countries in the
Middle East?
A. 2.65
B. 0.05
C. 3.01
D. 0
E. 0.024
4. The decision rule for the t-test to compare the mean child mortality rate for countries in Africa
with the mean child mortality rate for countries in South Asia
A.
Reject Ho, if the p-value is less than .05.
B.
F.T.R. Ho, if the p-value is less than .05.
C.
Reject Ho, if the p-value is greater than .05.
D.
Reject Ha, if the p-value is greater than .05.
E.
F.T.R. Ho, if the p-value is equal to .05.
5. What is the conclusion for t-test concerning if the mean child mortality rate for countries in
South East Asia is more than the mean Child mortality rate for countries in Western Europe by
more than 10 per thousand?
A.
There is evidence that the mean child mortality rate for countries in South East Asia is more
than the mean Child mortality rate for countries Western Europe by more than 10 per
thousand.
B.
There is insufficient evidence that the mean child mortality rate for countries in
South East Asia is more than the mean Child mortality rate for countries Western
Europe by more than 10 per thousand.
C.
There is insufficient evidence that the mean child mortality rate for countries in South East
Asia is equal to Child mortality rate for countries Western Europe by more than 10 per
thousand.
D.
There is conclusive evidence that the mean child mortality rate for countries in South East
Asia is more than the mean Child mortality rate for countries Western Europe by more than
10 per thousand.
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