Project - Phase 3

Course Project – Phase II

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

· What are confidence intervals?

a) A range (or an interval) of values used to estimate the true value of a population parameter

· What is a point estimate?

a) A single value used to approximate a population parameter

· What is the best point estimate for the population mean? Explain.

a) The sample mean is the best point estimate for the population mean; the sample mean is an unbiased estimator of the population mean, meaning that the distribution of sample means tend to center about the value of the population mean.

· Why do we need confidence intervals?

a) Confidence intervals are used to bind the mean or standard deviation, but can also be obtained for regression coefficients, proportions, rates of occurrence, and for the differences between populations.

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

· Find the best point estimate of the population mean.

a) Average (population mean) = 61.82; best point estimate = 0.6182

b)

· Construct a 95% confidence interval for the population mean. Assume that your data is normally distributed and Ã�Æ’ is unknown.

a) (SEE EXCEL DOCUMENT)

b) I am 95% confident that out of the 60 patients 2.3 of them are at a higher risk level for contracting the disease due to their age.

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

· Find the best point estimate of the population mean.

· Construct a 99% confidence interval for the population mean. Assume that your data is normally distributed and Ã�Æ’ is unknown.

a) (SEE EXCEL DOCUMENT)

b) I am 99% confident that out of the 60 patients 3.0 of them are at a higher risk level for contracting the disease due to their age.

4. Compare and contrast your findings for the 95% and 99% confidence interval.

· Did you notice any changes in your interval estimate?

a) There is a slightly higher interval level for the 99% confidence interval; however when comparing the upper & lower didn’t seem to be a huge difference between the two.

Course Project – Phase I

My data set involves patients admitted into NCLEX Memorial Hospital with a particular infectious disease. Over the past few days I have noticed an increase in patient admissions with a particular infectious disease. I believe that the ages of these patients play a critical role in the method used to treat the patients. Using statistical analysis and looking closely at the ages of the patients we can also determine if the patient’s age is correlated in contracting the disease. The date set consist of 60 patients, ranging in age from 35 to 76, with an infectious disease.

Variables:

· Quantitative: ages of patients

· Qualitative: patient number

· Discrete: Patient age; ratio is the level of measurement

· Continuous: Patient number; nominal is the level of measurement

Measures of center include: mean, median, and mode; these help give an idea of what the most common, normal, or representative answer might be. Measures of variation include: range, variance, standard deviation, and midrange; these describe how spread out or scattered a set of data is.

Calculations of the measures of center and the measures of variation:

AVERAGE	61.82
MEDIAN	61.50
MODE	69.00
MIDRANGE	55.5
VARIANCE	79.64379
STANDARD DEVIATION	8.924337

According to the numbers above the average age of the patients with an infectious disease is 62 years old; however there are more 69 year old patients have come to the hospital to be treated. Out of the 60 patients only 7 are below the age of 50. In my opinion there are definitive results that would lead me to believe that patients over the age of 50 are more likely to contract this infectious disease.