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## importance of constructing confidence intervals

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Instructions:importance of constructing confidence intervals

Deliverable 03 Worksheet

- Discuss the importance of constructing confidence intervals for the population mean by answering these questions.

- What are confidence intervals?
- What is a point estimate?
- What is the best point estimate for the population mean? Explain.
- Why do we need confidence intervals?
Answer and Explanation:

Enter your step-by-step answer and explanations here.

- Using the data from the Excel workbook, construct a 95% confidence interval for the population mean. Assume that your data is normally distributed and σ is unknown. Include a statement that correctly interprets the confidence interval in context of the scenario.
Hint: Use the sample mean and sample standard deviation from Deliverable 1.

Answer and Explanation:

Enter your step-by-step answer and explanations here.

- Using the data from the Excel workbook, construct a 99% confidence interval for the population mean. Assume that your data is normally distributed and σ is unknown. Include a statement that correctly interprets the confidence interval in context of the scenario.
Hint: Use the sample mean and sample standard deviation from Deliverable 1.

Answer and Explanation:

Enter your step-by-step answer and explanations here.

- Compare your answers for (2) and (3). You notice that the 99% confidence interval is wider. What is the advantage of using a wider confidence interval? Why would you not always use the 99% confidence interval? Explain with an example.
Answer and Explanation:

Enter your step-by-step answer and explanations here.

- We want to estimate the mean salary in Minnesota. How many jobs must be randomly selected for their respective mean salaries if we want 95% confidence that the sample mean is within $126 of the population mean and σ = $1150.
Is the current sample size of 364 in the data set in our Excel workbook large enough? Explain.

Answer and Explanation:

Enter your step-by-step answer and explanations here.

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