Questions: According to a food website, the mean consumption of popcorn annually by Americans is 64 quarts. The marketing division of the food website unleashes an aggressive campaign designed to get Americans to consume even more popcorn. Complete parts (a) through (c) below. (a) Determine the null and alternative hypotheses that would be used to test the effectiveness of the marketing campaign. H0: H1: (Type integers or decimals. Do not round.)

According to a food website, the mean consumption of popcorn annually by Americans is 64 quarts. The marketing division of the food website unleashes an aggressive campaign designed to get Americans to consume even more popcorn. Complete parts (a) through (c) below.

(a) Determine the null and alternative hypotheses that would be used to test the effectiveness of the marketing campaign.
H0:
H1:
(Type integers or decimals. Do not round.)
Transcript text: According to a food website, the mean consumption of popcorn annually by Americans is 64 quarts. The marketing division of the food website unleashes an aggressive campaign designed to get Americans to consume even more popcorn. Complete parts (a) through (c) below. (a) Determine the null and alternative hypotheses that would be used to test the effectiveness of the marketing campaign. $\mathrm{H}_{0}$ : $\square$ $\square$ $\square$ $\mathrm{H}_{1}$ : $\square$ $\square$ $\square$ (Type integers or decimals. Do not round.)
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Solution

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Solution Steps

Step 1: Define the Hypotheses

To test the effectiveness of the marketing campaign aimed at increasing popcorn consumption, we establish the following hypotheses:

  • Null Hypothesis (\(H_0\)): The mean consumption of popcorn annually by Americans is \( \mu = 64 \) quarts.
  • Alternative Hypothesis (\(H_1\)): The mean consumption of popcorn annually by Americans is greater than \( \mu = 64 \) quarts.
Step 2: Determine the Test Type

Since we are interested in whether the mean consumption has increased, we will conduct a right-tailed test. This means we will be looking for evidence that the sample mean is significantly greater than 64 quarts.

Step 3: Expected Output Format

If we had the sample data, we would compute the following statistics:

  • Test Statistic: \( \text{result['test_statistic']} \)
  • P-value: \( \text{result['p_value']} \)
  • Standard Error: \( \text{result['standard_error']} \)
  • Sample Mean: \( \text{result['sample_mean']} \)
  • Sample Standard Deviation: \( \text{result['sample_standard_deviation']} \)

These values would provide insight into whether we can reject the null hypothesis in favor of the alternative hypothesis.

Final Answer

The hypotheses for the test are:

  • \(H_0: \mu = 64\)
  • \(H_1: \mu > 64\)

The expected output format for the test results is as follows:

  • Test Statistic: \( \text{result['test_statistic']} \)
  • P-value: \( \text{result['p_value']} \)
  • Standard Error: \( \text{result['standard_error']} \)
  • Sample Mean: \( \text{result['sample_mean']} \)
  • Sample Standard Deviation: \( \text{result['sample_standard_deviation']} \)

Thus, the final boxed answer is: \[ \boxed{H_0: \mu = 64, \quad H_1: \mu > 64} \]

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