Compile the drafts prepared in the milestone assignments, incorporating feedback from your instructor. Finalize the PowerPoint presentation by adding either voice narration for each slide or a transcript in the notes section.Before submitting the assignment, carefully re-read the Final Project Guidelines and Rubric document, paying close attention to the critical elements and the rubric.Once you have submitted your assignment here, also post it to the Module Ten discussion topic. Your classmates will review and comment on your project in the next module.

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 County Data document 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 median listing price and the predictor variable (x) should be the median 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 median listing price and the median square foot variables. Analyze Your Sample Discuss how the regional sample created is reflective of the national market.  Compare and contrast your sample with the population using the National Statistics and Graphs 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 yvariables noted above and include a trend line. 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 1,200 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? PART 2: Prompt This assignment picks up where the Module Two assignment left off and will use components of that assignment as a foundation. You have submitted your initial analysis to the sales team at D.M. Pan Real Estate Company. You will continue your analysis of the provided Real Estate County Data spreadsheet using your selected region to complete your analysis. You may refer back to the initial report you developed in the Module Two Assignment Template to continue the work. This document and the National Statistics and Graphsspreadsheet will support your work on the assignment. Note: In the report you prepare for the sales team, the dependent, or response, variable (y) should be the median listing price and the independent, or predictor, variable (x) should be the median square feet. Using the Module Three Assignment Template, specifically address the following: Regression Equation: Provide the regression equation for the line of best fit using the scatterplot from the Module Two assignment. Determine r: Determine r and what it means. (What is the relationship between the variables?) Determine the strength of the correlation (weak, moderate, or strong). Discuss how you determine the direction of the association between the two variables. Is there a positive or negative association? What do you see as the direction of the correlation? Examine the Slope and Intercepts:Examine the slopeb1b1 and intercept b0b0 Draw conclusions from the slope and intercept in the context of this problem. Does the intercept make sense based on your observation of the line of best fit? Determine the value of the land only. Note: You can assume, when the square footage of the house is zero, that the price is the value of just the land. This happens when x=0, which is the y-intercept. Determine the R-squared Coefficient:Determine the R-squared value. Discuss what R-squared means in the context of this analysis. Conclusions: Reflect on the Relationship: Reflect on the relationship between square feet and sales price by answering the following questions: Is the square footage for homes in your selected region different than for homes overall in the United States? For every 100 square feet, how much does the price go up (i.e., can you use slope to help identify price changes)? Use the regression equation to estimate how much you would list your house for if it was 1,200 square feet. What square footage range would the graph be best used for?