Evidence implicates infection with human papilloma virus as a risk factor for cervical cancer. There are over forty (40) strains of HPV. Some evidence indicates that there may be a relationship between the strain of human papillomavirus (HPV) infection and the risk of cervical cell abnormalities. A few of these strains are deemed “high-risk”, while others are deemed “low risk”. For our purposes here, we will consider any HPV virus as belonging to either a low- or high-risk strain.

Address each of the following six (6) items. Each item is worth twenty five (25) points.

1. State a null hypothesis and an alternative hypothesis.

2. Determine the level of the variables:
a. If HPV infection is measured as not infected, infected with a low-risk strain, or infected with a high-risk strain, what level of measurement is this variable?
b. If cervical cell abnormalities are measured as biopsy pathology results of negative, CIN I, CIN II, CIN III, or Cancer in Situ (these are progressively worse levels of abnormality), what level of measurement is the variable?
3. Use Figure tableable Choosing a Statistical Test
Independent
Variables (IVs) Dependent Variable Statistical Tests
0 IV
Interval & normal
Categorical
One-sample t-test
χ2 test of goodness of fit
1 categorical IV with 2 levels (independent)
Interval & normal
Ordinal or interval
Categorical
Independent t-test
Wilcoxon/Mann–Whitney test
χ2/Fisher’s exact test
1 categorical IV with 2 levels (dependent)
Interval & normal
Ordinal or interval
Categorical
Dependent t-test
Wilcoxon signed rank test
McNemar test
1 categorical IV with more than 2 levels (independent)
Interval & normal
Ordinal or interval
One-way analysis of variance (ANOVA)
Kruskal–Wallis test
1 categorical IV with more than 2 levels (dependent)
Interval & normal
Ordinal or interval
Categorical
One-way repeated measures ANOVA
Friedman test
Repeated measures logistic regression
2 or more categorical IVs (independent)
Interval & normal
Categorical
Factorial ANOVA
Factorial logistic regression
1 interval IV
Interval & normal
Ordinal or interval
Categorical
Correlation (Pearson’s)/simple linear regression
Nonparametric correlation (Spearman’s rho)
Simple logistic regression
1 or more interval IVs and/or 1 or more categorical IVs
Interval & normal
Categorical
Multiple regression/analysis of covariance (ANCOVA)
Logistic regression/discriminant analysis
Steps 5 and 6: Running the Proposed Test and Finding the Critical Value

As we proceed in this text, we will discuss each test and how to select the necessary options in SPSS.
Step 7:

4. Compare the following population results from past studies with the sampled results from the current study to determine whether the sample is representative. Show your work and explain your rationale.
In the population, 30% of cervical biopsies are negative, 40% are CIN I, 20% are CIN II, 5% are CIN III, and 5% are Cancer in Situ (CIS). A random selection of hospitals is made and a random selection of biopsy results is reviewed.
In the random sample of 120 biopsies, 16 are negative, 42 are CIN I, 30 are CIN II, 22 are CIN III, and 10 are CIS. In the same sample, 1 person is HPV negative, 87 are HPV positive with the low-risk strain, and 32 are HPV positive with the high-risk strain.
5. Answer the following questions based on below scenario.
Suppose the statistical test you employ states that the association between the type of HPV infection and cervical cell abnormalities has a p-value of 0.06. If the alpha for the study is set at 0.05,
a. What should the researcher conclude regarding the null hypothesis? Why?
b. If instead of an alpha of 0.05 the researchers decided to set this pilot study’s alpha at 0.10, what would the researcher conclude about the null hypothesis (p = 0.06)?
6. Address the following issues:
a. If the researcher rejects the null hypothesis but does so in error, what type of error could he or she be making? What does this type of error mean?
b. If the researcher does find a statistically significant difference, does this mean it is a clinically significant difference?

The specific course learning outcomes associated with this assignment are:

Describe the basic logic of hypothesis testing.
Use technology and information resources to research issues in statistical concepts for healthcare.
Write clearly and concisely about statistical concepts for healthcare using proper writing mechanics.