The Economist collects data each year on the price of a Big Mac in various countries around the world. A sample of McDonald's restaurants in Europe in July 2016 resulted in the following Big Mac prices (after conversion to U.S. dollars). Find the test statistic

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The Economist collects data each year on the price of a Big Mac in various countries around the world. A sample of McDonald's restaurants in Europe in July 2016 resulted in the following Big Mac prices (after conversion to U.S. dollars).

Find the test statistic 

**Big Mac Price Analysis: Hypothesis Testing**

**Introduction**

The Economist collects data each year on the price of a Big Mac in various countries around the world. A sample of McDonald's restaurants in Europe in July 2016 resulted in the following Big Mac prices (after conversion to U.S. dollars):

- Price Sample: 4.41, 3.13, 2.45, 3.98, 4.35, 4.51, 4.14, 3.72, 4.60, 3.78, 3.37, 3.88.

**Hypothesis Testing Overview**

The mean price of a Big Mac in the U.S. in July 2016 was $5.04. For purposes of this exercise, you can assume it is reasonable to regard the sample as representative of European McDonald's restaurants. Does the sample provide convincing evidence that the mean July 2016 price of a Big Mac in Europe is less than the reported U.S. price?

Test the relevant hypotheses using \(\alpha = 0.05\).

**Steps in Hypothesis Testing**

1. **State the Hypotheses:**

   - Null Hypothesis (\(H_0\)): \(\mu = 5.04\)
   - Alternative Hypothesis (\(H_a\)): \(\mu < 5.04\)

2. **Finding the Test Statistic and P-value:**

   - Calculate the test statistic (\(t\)) and P-value, rounding the test statistic to one decimal place and the P-value to three decimal places.

**Conclusion**

- *Test Statistic:* Not provided (denoted by a cross).
- *P-value:* 0.000

This analysis framework assists in understanding whether the sample data provides evidence that the average price of a Big Mac in Europe in July 2016 is statistically significantly less than the U.S. price.
Transcribed Image Text:**Big Mac Price Analysis: Hypothesis Testing** **Introduction** The Economist collects data each year on the price of a Big Mac in various countries around the world. A sample of McDonald's restaurants in Europe in July 2016 resulted in the following Big Mac prices (after conversion to U.S. dollars): - Price Sample: 4.41, 3.13, 2.45, 3.98, 4.35, 4.51, 4.14, 3.72, 4.60, 3.78, 3.37, 3.88. **Hypothesis Testing Overview** The mean price of a Big Mac in the U.S. in July 2016 was $5.04. For purposes of this exercise, you can assume it is reasonable to regard the sample as representative of European McDonald's restaurants. Does the sample provide convincing evidence that the mean July 2016 price of a Big Mac in Europe is less than the reported U.S. price? Test the relevant hypotheses using \(\alpha = 0.05\). **Steps in Hypothesis Testing** 1. **State the Hypotheses:** - Null Hypothesis (\(H_0\)): \(\mu = 5.04\) - Alternative Hypothesis (\(H_a\)): \(\mu < 5.04\) 2. **Finding the Test Statistic and P-value:** - Calculate the test statistic (\(t\)) and P-value, rounding the test statistic to one decimal place and the P-value to three decimal places. **Conclusion** - *Test Statistic:* Not provided (denoted by a cross). - *P-value:* 0.000 This analysis framework assists in understanding whether the sample data provides evidence that the average price of a Big Mac in Europe in July 2016 is statistically significantly less than the U.S. price.
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Many fundraisers ask for donations using email and text messages. A paper describes an experiment to investigate whether the proportion of people who make a donation when asked for a donation by email is different from the proportion of people who make a donation when asked for a donation in a text message. In this experiment, 1.5% of those who received and opened an email request for a donation and 7.2% of those who received a text message asking for a donation actually made a donation. Assume that the people who received these requests were randomly assigned to one of the two groups (email or text message) and suppose that the given percentages are based on sample sizes of 2,000 (the actual sample sizes in the experiment were much larger). (Let p1 be the proportion who make a donation after receiving an email, and p2 be the proportion who make a donation after receiving a text message.)

 

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