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A nutrition store in the mall is selling 'memory booster' which is a concoction of herbs and minerals that is intended to improve memory performance. To test the effectiveness of the herbal mix, a researcher obtains a sample of n = 16 people and has each person take the suggested dosage each day for 4 weeks. At the end of the four-week period, each individual takes a standardized memory test. The scores from the sample produced a mean of m = 26 with a sample variance of s² = 64. In the general population, the standardized test is known to have a mean of μ = 20. Do the sample data support the conclusion that the memory?

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Final answer:

The sample data supports the conclusion that the memory booster is effective at improving memory performance.

Step-by-step explanation:

To test the effectiveness of the 'memory booster' herbal mix, the researcher obtained a sample of n = 16 people and had each person take the suggested dosage each day for 4 weeks. At the end of the four-week period, each individual took a standardized memory test.

The sample produced a mean of m = 26 with a sample variance of s² = 64. In the general population, the standardized test is known to have a mean of μ = 20.

We will conduct a hypothesis test to determine if the sample data supports the conclusion that the memory booster is effective at improving memory performance.

Step 1: Define the null and alternative hypotheses

The null hypothesis (H0) states that the mean memory test score for people who take the 'memory booster' is the same as the general population mean, μ = 20. The alternative hypothesis (Ha) states that the mean memory test score for people who take the 'memory booster' is greater than the general population mean, μ > 20.

H0: μ = 20

Ha: μ > 20

Step 2: Choose a significance level

We will use a significance level of α = 0.05, which means we are willing to accept a 5% chance of rejecting the null hypothesis when it is actually true.

Step 3: Conduct the hypothesis test

We will use a one-sample t-test to compare the sample mean of m = 26 to the population mean μ = 20. We have a small sample size (n = 16), so the t-test is appropriate.

Using the sample mean, sample variance, and sample size, we can calculate the t-statistic:

t = (m - μ) / (s / sqrt(n))

Where:

m is the sample mean: 26

μ is the population mean: 20

s is the sample standard deviation: sqrt(64) = 8

n is the sample size: 16

t = (26 - 20) / (8 / sqrt(16))

t = 6 / (8 / 4)

t = 6 / 2

t = 3

Using a t-table or statistical software, we can find the critical t-value for a one-tailed test with a significance level of α = 0.05 and degrees of freedom (df) = n - 1 = 16 - 1 = 15. The critical t-value is approximately 1.753.

Since the calculated t-value of 3 is greater than the critical t-value of 1.753, we reject the null hypothesis.

Step 4: Interpret the results

The sample data supports the conclusion that the 'memory booster' is effective at improving memory performance. The mean memory test score for people who take the 'memory booster' is significantly higher than the general population mean.

User Darren Kopp
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