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A student organization uses the proceeds from a particular soft-drink dispensing machine to finance its activities. The price per can had been $0.75 for a long time, and the mean daily revenue during that period was $75.00. The price was recently increased to $1.00 per can. A random sample of n =21 days after the price increase yielded a sample mean daily revenue and sample standard deviation of $70.00 and $4.10, respectively. Does this information suggest that the mean daily revenue has decreased from its value before the price increase?

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Yes, there is a significant decrease in the mean daily revenue after the price increase. The p-value is 9.0257e-06, which is less than 0.05.

To determine whether there has been a significant decrease in the mean daily revenue after the price increase, we can perform a two-sample t-test. Here's the hypothesis testing procedure:

1. Null Hypothesis (H₀): There is no difference in the mean daily revenue before and after the price increase. Symbolically, H₀: μ₁ - μ₂ = 0, where μ₁ is the mean daily revenue before the price increase and μ₂ is the mean daily revenue after the price increase.

2. Alternative Hypothesis (H₁): The mean daily revenue has decreased after the price increase. Symbolically, H₁: μ₁ - μ₂ > 0.

3. Significance Level (α): Let's assume α = 0.05.

4. Test Statistic: The t-test statistic is given by the formula:

t = (X₁ - X₂) / (s / √n)

where:

- X₁ is the mean daily revenue before the price increase ($75.00)

- X₂ is the mean daily revenue after the price increase ($70.00)

- s is the pooled standard deviation

- n is the total sample size (41 days)

5. P-value: The p-value is the probability of obtaining a test statistic as extreme or more extreme than the observed one, assuming the null hypothesis is true. A small p-value indicates that the observed difference is unlikely to have occurred by chance alone, providing evidence against the null hypothesis.

6. Decision: Compare the p-value to the significance level (α).

- If p-value ≤ α, reject the null hypothesis and conclude that there is a significant decrease in the mean daily revenue after the price increase.

- If p-value > α, fail to reject the null hypothesis and conclude that there is not enough evidence to support the claim that the mean daily revenue has decreased.

Calculating the test statistic and p-value using the given data:

t = (75.00 - 70.00) / (4.10 / √41) = 2.44

p-value ≈ 0.019

Since the p-value (0.019) is less than the significance level (0.05), we reject the null hypothesis and conclude that there is a significant decrease in the mean daily revenue after the price increase. This suggests that the price increase has negatively impacted the organization's revenue.

User Akheloes
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