# Statistics: Phase 5 of the Course Project

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oynpdhr6978

Mathematics

## Description

Below is a summary of the expectations for Phase 5 of the course project:

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 a 95% confidence interval for the population mean. Assume that your data is normally distributed and σ 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.
• Write 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 a 99% confidence interval for the population mean. Assume that your data is normally distributed and σ 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.
• Write 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?
• 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 α = 0.05 and assume your data is normally distributed and σ is unknown.
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?
What is the critical value?
5. What is your decision; reject the null or do not reject the null?
1. Explain why you made your decision including the results for your p-value and the critical value.
6. State the final conclusion in non-technical terms.
1. Conclusion
• Recap your ideas by summarizing the information presented in context of your chosen scenario.
Please be sure to show all of your work and use the Equation Editor to format your equations.
 This assignment should be formatted using APA guidelines and a minimum of 2 pages in length.

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Attached.

Running head: PHASE 5 OF THE COURSE PROJECT

Phase 5 of the Course Project
Name
Institution

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PHASE 5 OF THE COURSE PROJECT

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Introduction
Statistical analysis focuses on both descriptive and inferential statistics. Descriptive
statistics provide crucial information in understanding the underlying characteristics of the
variables that have been included in the research. Inferential statistics give a more significant
commitment to the underlying research assumptions involved in the analysis which need to
be verified. The dataset that has been included in the study provides focus on patients
admitted with infectious disease and their respective age. Thus the data can be used to
determine different aspects based on the research objective. The variables included in the
analysis include patient ID, Infectious disease status and age. Infectious disease is a
categorical variable which is measured on an ordinal scale while age is a continuous variable
that is measured on a ratio scale.
The importance of the Measures of Center and the Measures of Variation
The measures of central tendency provide crucial information regarding the
distribution of the dataset while the measures of variation give a greater emphasis on the
spread of data where it is possible to determine necessary changes which help in maintaining
better understanding on the information provided.
The measures of center provide a crucial focus on the normality of the distribution. It
helps in understanding the characteristics of the variables included in the analysis.
Determination of these concepts is essential in determining whether there are outliers in the
dataset provided.
The measures of variation highlight the spread of the data around the central values
that have been determined. Making a better determination on the existing variation provide a
string basis where it is possible to understa...

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