Hypothesis Testing Examples and Solutions - Biostatistics BST 601

This assignment provides several examples of hypothesis testing scenarios in biostatistics. The examples cover various statistical methods, including independent and dependent t-tests, ANOVA, and multiple regression. Each example includes the presentation of null and alternative hypotheses, definition of independent and outcome variables, justification for the chosen statistical method, and conclusions based on statistically significant results. The scenarios cover topics such as the effect of yoga on blood pressure, the relationship between altitude, age, and blood pressure, and the effectiveness of a new migraine drug. Desklib offers a platform for students to access similar solved assignments and past papers for academic support.

Example 1
I want to check whether doing yoga regularly can lead to lower BP or not. Two groups are
selected and one of these groups does yoga for 1 hour daily while the other group does not.
1) Present your null and alternative hypotheses
H0: μ1= μ2 i.e. no difference in the mean BP between the two groups
H1: μ1< μ2 i.e. the group doing Yoga has a mean BP lower than the other group not doing
Yoga.
2) Define your independent and outcome variables
Independent Variable: Exposure to Yoga or not
Outcome variable: Blood Pressure
3) Indicate the method you will use and why you will use it
Two independent sample t test would be used. Since population deviation is not known,
hence t statistic would be used. The two sample are independent and have numerical values.
4. Assume your result will be statistically significant and what your conclusions will be since
it is
H0 is rejected and alternative hypothesis is accepted. As a result, it can be concluded that
Yoga is indeed effective in reduction of blood pressure in significant manner.
Example 2
I want to check if the mean blood pressure level of individuals is linked to the altitude at
which they stay and their age. As a result, the data for 200 people has been collected.
1) Present your null and alternative hypotheses
H0: β1= β2 = 0 i.e. each of the two slopes is insignificant and hence can be assumed to be zero.
H1: Atleast one of the slopes is significant and hence non-zero.
2) Define your independent and outcome variables
Independent Variable: Altitude, Age
Outcome variable: Blood Pressure

3) Indicate the method you will use and why you will use it
In the multiple regression analysis, the ANOVA output would be generated which would be
used to test the significance of the multiple regression model. The F statistics and
corresponding p value would be used.
4) Assume your result will be statistically significant and what your conclusions will be since
it is
H0 is rejected and alternative hypothesis is accepted. As a result, it can be concluded that the
multiple linear regression model is significant.
Example 3
A new drug that tends to prevent the incidence of migraine wants to be tested. A given
sample of migraine patients is selected and their migraine incidence during a 30 day period is
recorded. Then, each of the each sample patients are given the drug and again the migraine
incidence during a 30 day period is recorded. The objective is to determine if the drug is
effective.
1) Present your null and alternative hypotheses
H0: μ1 - μ2= 0 i.e. there is no difference between the mean incidence of migraine before and
after the drug
H1: μ1 - μ2>0 i.e. the incidence of migraine before the drug was higher in comparison to after
the drug.
2) Define your independent and outcome variables
Independent variable: Administration of drug
Dependent variable : Incidence of migraine during a 30 day period
3) Indicate the method you will use and why you will use it
The dependent t test would be used as there are not two samples but instead one sample and
before and after comparison is being performed. This is used as there would be dependence
between the before and after samples owing to the underlying respondents being same.
4) Assume your result will be statistically significant and what your conclusions will be since
it is

H0 is rejected and alternative hypothesis is accepted. As a result, it can be concluded that the
drug is effective in reducing the incidence of migraine.