Question

A researcher conducted an experiment to investigate the effectiveness of a medicated lotion in treating a skin irritation. A group of 80 people with a history of skin irritation volunteered for the study. Of the 80 people, 40 were randomly assigned the medicated lotion, and the remaining 40 were given a nonmedicated lotion. At the end of one month, the skin irritation had cleared for 36 people (90 percent) using the medicated lotion and 16 people (40 percent) using the nonmedicated lotion. Analysis of the results showed the difference was statistically significant. What can be concluded from the experiment?

Answer 1

Answer:

It can be concluded that the medicated lotion has an effect on treating skin irritations.

Step-by-step explanation:

In this case we need to determine whether the medicated lotion was effective in treating the skin irritation or not.

The hypothesis can be defined as follows:  

H₀: There is no difference between the two proportions, i.e. p₁ - p₂ = 0.  

Hₐ: There is a significant difference between the two proportions, i.e. p₁ - p₂ ≠ 0.  

The information provided is:

n₁ = 40

n₂ = 40

X₁ = 36

X₂ = 16

Compute the sample proportions and total proportions as follows:

 $\hat p_{1}=\frac{36}{40}=0.90\\\\\hat p_{2}=\frac{16}{40}=0.40\\\\\hat P=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{36+16}{40+40}=0.65$

Compute the test statistic value as follows:

 $z=\frac{\hat p_{1}-\hat p_{2}}{\sqrt{\hat P(1-\hat P)[\frac{1}{n_{1}}+\frac{1}{n_{2}}]}}=\frac{0.90-0.40}{\sqrt{0.65(1-0.65)[\frac{1}{40}+\frac{1}{40}]}}=4.69$

The test statistic value is 4.69.

The decision rule is:

The null hypothesis will be rejected if the p-value of the test is less than the significance level.

Compute the p-value as follows:

 $p-value=2\times P(Z$

The p-value of the test is very small.

The null hypothesis will be rejected at any significance level.

Thus, there is a significant difference between the two proportions.

So, it can be concluded that the medicated lotion has an effect on treating skin irritations.