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1. UOP MHA 610 Week 6 Assignment Final Project
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Final Project. In this final assignment, we will
revisit datasets that we have utilized in previous
assignments, but with new objectives.
• In the Week One assignment, you looked at
mortality in your particular state, with two
different metrics: the first was numbers of deaths,
and the second was years of life lost. For this
question, return to the original dataset, but this
time first pool all cancer causes of death together,

2. so that cancer constitutes the only category for
cause of death. Then, repeat your analyses from
Week One. How do your conclusions change?
• In the Week Two assignment, you looked at sex
ratios for births in your state.
o Take the data you have assembled from the
second part of your Week Two assignment,
namely, numbers of first-born boy and girl births
in your state between 2007 and 2012, separately
by racial group (i.e., American Indians, Asians,
Blacks, and Whites). Form a two-by-four
contingency table from these data: the two row
categories are female (girl) and male (boy), and
the four column categories are the four racial
groups. Calculate the chi-square statistic from this
contingency table, and interpret the result.
o Return to the CDC Wonder website, and obtain
the numbers of births in your state between 2007
and 2012, by month. (Disregard gender, or race, or
birth order—you want all births). Calculate a chi-
square statistic to assess whether there is any
seasonality to births. (Your null hypothesis is that
births should be equally likely to occur in any of
the 12 months. We are ignoring the varying
lengths of the months to simplify calculations.)

3. How would you interpret your findings? Explain in
500 words in APA format supported by scholarly
sources.
BONUS: Give a graphical representation of your
findings for this portion highlighting what you
consider significant.
• In the Week Three assignment, you were given
levels of tumor-associated antigens in a sample of
90 normal (non-cancer) individuals, and 160
hepatocellular carcinoma (HCC) patients. Here is a
proposed diagnostic test for HCC:
o For each individual, calculate a numerical score:
score = -3.95 + 10.7 * HCC1 - 4.14 * P16 + 13.95 *
P53 + 28.92 * P90 + 6.48 * survivin♣
(This equation was derived from logistic
regression.)♣
o If this score is positive (i.e., > 0), diagnose this
individual as an HCC patient; if this score is
negative (i.e., <0), diagnose this individual as
normal (i.e., non-cancer).

4. o Apply this rule to the entire cohort of 250
individuals. Report the sensitivity of this rule, the
specificity, the false positive rate, the false
negative rate, and the overall accuracy. Do you
think the score function provides a good
diagnostic test for HCC? Explain.
• In the Week Four assignment, we considered a
simple two-by-two crossover trial of a new
experimental treatment for interstitial cystitis. We
calculated t tests for carryover and treatment
effects, but we have not yet considered period
effects. It is unlikely that there are any period
effects in this trial, but we may want to test this
formally. If there were a period effect, then patient
responses under either treatment would likely be
systematically higher in one period than the other.
(Here's an analogy: Think of taking the same test
twice. You would likely perform better on the test
the second time, since you have learned from your
experience of taking the first test.) Explain how
you would devise a t test for assessing a period
effect in this trial. (Hint: look at the explanation of
the t test for treatment effects given in the Week
Four assignment. There, we based the test on the
random variable X - Y. Suppose we look instead at
X + Y?)

5. • In the Week Five assignment, you investigated
measures of brain size and intelligence in a sample
of 20 youths. A potential shortcoming of your prior
analyses is that you did not take into account all
available information in the dataset, in particular,
gender. Answer the following questions and
explain your answers:
o Do any of the physiologic variables CCSA, HC,
TOTSA, TOTVOL, and WEIGHT differ significantly
between males and females?
o Do IQs differ significantly by gender?
o Undertake a paired analysis of IQs, in order to
assess whether firstborns have higher IQs than
non-firstborns. In this regard, there are 10 pairs of
related youths, as denoted by the variable PAIR.
Completing the Final Project
The Final Project:
1. Must include a title page with the following:
a. Title of paper
b. Student’s name
c. Course name and number

6. d. Instructor’s name
:2. Must begin with an introductory paragraph that
has a succinct thesis statement.
3. Must address the topic of the paper with critical
thought.
4. Must end with a conclusion that reaffirms your
thesis.
5. Must use a minimum of 3-5 scholarly, peer-
reviewed sources published within the last five
years (not including the course text) or those
applicable to the data sets.
6. Must document all sources in APA style, as
outlined in the Ashford Writing Center.
7. Must include a separate reference page,
formatted according to APA style as outlined in the
Ashford Writing Center. The number of pages must
be applicable to the specific data sets outlined in
the Final Project assignment.

7. d. Instructor’s name
:2. Must begin with an introductory paragraph that
has a succinct thesis statement.
3. Must address the topic of the paper with critical
thought.
4. Must end with a conclusion that reaffirms your
thesis.
5. Must use a minimum of 3-5 scholarly, peer-
reviewed sources published within the last five
years (not including the course text) or those
applicable to the data sets.
6. Must document all sources in APA style, as
outlined in the Ashford Writing Center.
7. Must include a separate reference page,
formatted according to APA style as outlined in the
Ashford Writing Center. The number of pages must
be applicable to the specific data sets outlined in
the Final Project assignment.