1. Introduce your scenario and data set.

• Provide a brief overview of the scenario you are given above and the data set that you will be analyzing.
• Classify the variables in your data set.
• Which variables are quantitative/qualitative?
• Which variables are discrete/continuous?
• Describe the level of measurement for each variable included in your data set.

1. Discuss the importance of the Measures of Center and the Measures of Variation.

• What are the measures of center and why are they important?
• What are the measures of variation and why are they important?

1. Calculate the measures of center and measures of variation. Interpret your results in context of the selected topic.

• Mean
• Median
• Mode
• Midrange
• Range
• Variance
• Standard Deviation

1. Discuss the importance of constructing confidence intervals for the population mean.

• 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?

1. Based on your selected topic, evaluate the following:

• Find the best point estimate of the population mean.
• Construct a95%confidence interval for the population mean. Assume that your data is normally distributed and is unknown.
• Please show your work for the construction of this confidence interval and be sure to use the Equation Editor to format your equations.
• Create a statement that correctly interprets the confidence interval in context of your selected topic.

1. Based on your selected topic, evaluate the following:

• Find the best point estimate of the population mean.
• Construct a99%confidence interval for the population mean. Assume that your data is normally distributed and is unknown.
• Please show your work for the construction of this confidence interval and be sure to use the Equation Editor to format your equations.
• Create a statement that correctly interprets the confidence interval in context of your selected topic.
• Compare and contrast your findings for the 95% and 99% confidence interval.
• Did you notice any changes in your interval estimate? Explain.
• What conclusion(s) can be drawn about your interval estimates when the confidence level is increased? Explain.

1. Discuss the process for hypothesis testing.

• Discuss the 8 steps of hypothesis testing?
• When performing the 8 steps for hypothesis testing, which method do you prefer; P-Value method or Critical Value method? Why?

1. Perform the hypothesis test.

• If you selected Option 2:
• Original Claim: The average age of all patients admitted to the hospital with infectious diseases is less than 65 years of age.
• Test the claim using = 0.05 and assume your data is normally distributed and is unknown.
• Based on your selected topic, answer the following:

1. Write the null and alternative hypothesis symbolically and identify which hypothesis is the claim.
2. Is the test two-tailed, left-tailed, or right-tailed? Explain.
3. Which test statistic will you use for your hypothesis test; z-test or t-test? Explain.
4. What is the value of the test-statistic? What is the P-value?
5. What is the critical value?
6. What is your decision; reject the null or do not reject the null?
7. Explain why you made your decision including the results for your p-value and the critical value.
8. State the final conclusion in non-technical terms.
9. Conclusion

• Recap your ideas by summarizing the information presented in context of your chosen scenario.

option 2:

As a healthcare professional, you will work to improve and maintain the health of individuals, families, and communities in various settings.Basic statistical analysis can be used to gain an understanding of current problems.Understanding the current situation is the first step in discovering where an opportunity for improvement exists.This project will assist you in applying basic statistical principles to a fictional scenario in order to impact the health and wellbeing of the clients being served.

You are currently working at Grady Memorial Hospital in the Infectious Diseases Unit. Over the past few days, you have noticed an increase in patients admitted with a particular infectious disease. You believe that the ages of these patients play a critical role in the method used to treat the patients. You decide to speak to your manager and together you work to use statistical analysis to look more closely at the ages of these patients.You do some research and put together a spreadsheet of the data that contains the following information:

Client number

Infection Disease Status

Age of the patient

You need the preliminary findings immediately so that you can start treating these patients. So let's get to work!!!!

The data set consists of 60 patients that have the infectious disease with ages ranging from 35 years of age to 76 years of age for Grady Memorial Hospital.

Data:

Patient # Infectious Disease Age 1 Yes 69 2 Yes 35 3 Yes 60 4 Yes 55 5 Yes 49 6 Yes 60 7 Yes 72 8 Yes 70 9 Yes 70 10 Yes 73 11 Yes 68 12 Yes 72 13 Yes 74 14 Yes 69 15 Yes 46 16 Yes 48 17 Yes 70 18 Yes 55 19 Yes 49 20 Yes 60 21 Yes 72 22 Yes 70 23 Yes 76 24 Yes 56 25 Yes 59 26 Yes 64 27 Yes 71 28 Yes 69 29 Yes 55 30 Yes 61 31 Yes 70 32 Yes 55 33 Yes 45 34 Yes 69 35 Yes 54 36 Yes 48 37 Yes 60 38 Yes 61 39 Yes 50 40 Yes 59 41 Yes 60 42 Yes 62 43 Yes 63 44 Yes 53 45 Yes 64 46 Yes 50 47 Yes 69 48 Yes 52 49 Yes 68 50 Yes 70 51 Yes 69 52 Yes 59 53 Yes 58 54 Yes 69 55 Yes 65 56 Yes 61 57 Yes 59 58 Yes 71 59 Yes 71 60 Yes 68