Final answer:
To compare the average time to prepare a meal between the two locations, we can perform a hypothesis test using a two-sample t-test and a significance level of 0.1. We can state the null and alternative hypotheses, calculate the test statistic and p-value, and make a decision based on the comparison of the p-value to the significance level. Finally, we can interpret the results and draw conclusions.
Step-by-step explanation:
To compare the average time to prepare a meal between the two locations, we can perform a hypothesis test. Since we are comparing two population means using sample data, we can use a two-sample t-test. The null hypothesis (H0) would be that there is no difference in the average time to prepare a meal between the two locations, while the alternative hypothesis (Ha) would be that there is a difference.
Step 1: State the hypotheses:
H0: µ1 = µ2 (The average time to prepare a meal is the same for both locations)
Ha: µ1 ≠ µ2 (The average time to prepare a meal is different for both locations)
Step 2: Determine the significance level (alpha) which is given as 0.1 in this case.
Step 3: Calculate the test statistic and p-value using the sample data and the formula for the two-sample t-test.
Step 4: Compare the p-value to the significance level to make a decision. If the p-value is less than the significance level (0.1), we reject the null hypothesis and conclude that there is a significant difference in the average time to prepare a meal between the two locations.
Step 5: Interpret the results and make conclusions based on the decision made in Step 4.