Assignment: Surveys and Response Rates

Running head: RELIABILITY AND VALIDITY 1

1

Hypothesis

Student’s Name

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Hypothesis: The New Tylenol Physiotherapy Medicine Reduces Muscular Pain

My hypothesis aims at testing the effectiveness of the newly introduced muscle pain medicine to the targeted population. In this case, the targeted population will be United States citizens.

As for the collection of my sample, I will make use of the stratified sampling technique. Since the U.S population is too large, it will be more feasible to save time and money by selecting a manageable population. As such, the stratified random sampling technique pertains to the division of the whole population into homogeneous groups which are often referred to as strata (Gaston, 2014). A probability sampling method shall be adopted for this setting. Consequently, I will select ten patient care facilities offering physiotherapy services for muscular pain. Thereafter, I will consider a random selection of patients in all then ten facilities and make the appropriate observation before and after the new Tylenol medicine has been administered.

For these cases, the variables will be the status or level of muscular pain before and after the medicine has been induced in the sampled population. In particular, the dependent variable will be the level/measure of muscular pain, and the independent variable will be the new Tylenol medicine used in physiotherapy. Dependent variables usually depend on other measurable factors and they are expected to vary in the event of experimental manipulation of independent variables (Berenson, Levine, Szabat & Krehbiel, 2015). On the other hand, independent variables are usually unaffected and normally used by an investigator to systematically manipulate the dependent variables.

Additionally, considering that the null hypothesis would seek to disapprove of an existing of a pain-relieving relationship between the new medicine and the muscular pain levels, I will consider the Type I and Type II errors. Specifically, Type I error is considered to be more serious as opposed to Type II. Type I error is a false positive and occurs when an investigator rejects the true null hypothesis while Type II error is an error of omission (Wong & Phua, 2016). Hence, to control the Type I error, I will minimize the Type II error and use a significance level of alpha as 0.05.

In more detail, using Ho as my null hypothesis, there is an insignificance difference in the levels of muscular pain before and after the new Tylenol medicine is induced to the sampled population. In terms of expression, it could be denoted as u1= u2. The expression outcome will be tested against the alternative hypothesis, H1 which would stipulate that the levels of muscular pain will be higher after the new medicine is used on the sampled population; u1> u2.

In case the p-value will be less than the alpha value of 0.05, I will have to reject the null hypothesis at a 5% significance level and therefore, I will establish that the muscular pain level reduced after the new medicine was used in the sampled population. On the other hand, by utilizing the confidence interval, I would be 95% confident that the mean difference before and after the introduction of the new medicine to the patients lies between -0.75 and 1.75. The mentioned values are hypothetical.

References

Berenson, M., Levine, D., Szabat, K. A., & Krehbiel, T. C. (2015). Basic business statistics: Concepts and applications. Pearson Higher Education AU.

Gaston, L. (2014). Hypothesis Testing Made Simple. CreateSpace Independent Publishing Platform.

Wong, K. C., & Phua, K. L. (2016). Statistics made simple for healthcare and social science professionals and students. Serdang: Universiti Putra Malaysia Press.

Stangor, C. (2015). Research methods for the behavioral sciences (5th ed.). Stamford, CT: Cengage Learning.