Category: Mathematics and statistics

Read/review the following resources for this activity:
OpenStax Textbook: Chapter 8
Lesson
Chamberlain University Library
Week 7 Lab TemplateLinks to an external site.
Scenario/Summary
The highlight of this week’s lab is confidence intervals and the use of these intervals in the health sciences. There is a short reading that specifically relates confidence intervals to health sciences and then you are asked to demonstrate your knowledge of confidence intervals by applying them in a practical manner.
Prepare
Download the Week 7 Lab Lecture Notes
Follow along with he Week 7 Lab Video and fill out the Week 7 Lab Lecture Notes as you watch the video. 
** I have attached the video you must follow along**
Instructions
Steps to Complete the Week 7 Lab
Step 1: Find these articles in the Chamberlain Library. Once you click each link, you will be logged into the Library and then click on “PDF Full Text”.
First Article: Confidence Intervals, Part 1 Links to an external site.
Second Article: Confidence Intervals, Part 2 Links to an external site.
Step 2: Consider the use of confidence intervals in health sciences with these articles as inspiration and insights.
Step 3: Using the data you collected for the Week 5 Lab (heights of 10 different people that you work with plus the 10 heights provided by your instructor), discuss your method of collection for the values that you are using in your study (systematic, convenience, cluster, stratified, simple random). What are some faults with this type of data collection? What other types of data collection could you have used, and how might this have affected your study?
Step 4: Now use the Week 6 Spreadsheet to help you with calculations for the following questions/statements.
a) Give a point estimate (mean) for the average height of all people at the place where you work. Start by putting the 20 heights you are working with into the blue Data column of the spreadsheet. What is your point estimate, and what does this mean?
b) Find a 95% confidence interval for the true mean height of all the people at your place of work. What      is the interval? [see screenshot below]
c) Give a practical interpretation of the interval you found in part b, and explain carefully what the output       means. (For example, you might say, “I am 95% confident that the true mean height of all of the              people in my company is between 64 inches and 68 inches”).
d) Post a screenshot of your work from the t value Confidence Interval for µ from the Confidence                  Interval tab on the Week 6 Excel spreadsheet
Step 5: Now, change your confidence level to 99% for the same data, and post a screenshot of this table, as well.
Step 6: Compare the margins of error from the two screenshots. Would the margin of error be larger or smaller for the 99% CI? Explain your reasoning.
Step 7: Save the Week 7 Lab document with your answers and include your name in the title.
Step 8: Submit the document.

Scenario
Smart businesses in all industries use data to provide an intuitive analysis of how they can get a competitive advantage. The real estate industry heavily uses linear regression to estimate home prices, as cost of housing is currently the largest expense for most families. Additionally, in order to help new homeowners and home sellers with important decisions, real estate professionals need to go beyond showing property inventory. They need to be well versed in the relationship between price, square footage, build year, location, and so many other factors that can help predict the business environment and provide the best advice to their clients.
Prompt
You have been recently hired as a junior analyst by D.M. Pan Real Estate Company. The sales team has tasked you with preparing a report that examines the relationship between the selling price of properties and their size in square feet. You have been provided with a Real Estate Data Spreadsheet spreadsheet that includes properties sold nationwide in recent years. The team has asked you to select a region, complete an initial analysis, and provide the report to the team.
Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet.
Specifically you must address the following rubric criteria, using the Module Two Assignment Template:
Generate a Representative Sample of the Data
Select a region and generate a simple random sample of 30 from the data.
Report the mean, median, and standard deviation of the listing price and the square foot variables.
Analyze Your Sample
Discuss how the regional sample created is or is not reflective of the national market.
Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDF document.
Explain how you have made sure that the sample is random.
Explain your methods to get a truly random sample.
Generate Scatterplot
Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes.
Observe patterns
Answer the following questions based on the scatterplot:
Define x and y. Which variable is useful for making predictions?
Is there an association between x and y? Describe the association you see in the scatter plot.
What do you see as the shape (linear or nonlinear)?
If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at?
Do you see any potential outliers in the scatterplot?
Why do you think the outliers appeared in the scatterplot you generated?
What do they represent?