Can I get a step-by-step for this project? I've already turned it in, but I am nervous about it and I want to be sure I've completed it correctly when it gets given back for us to update it; this will also help me in my notes. I often find I have trouble determining which numbers to use in each equation, so if whoever answers this could also note where and how each number is determined would be very helpful, as well, thank you. Here is the 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 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 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 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 y variables noted above and include a trend line and the regression equation
• 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?
• 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 slope b1 and the intercept b0.
  • 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. Does this value make sense in context?
• 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)?
  • What square footage range would the graph be best used for?

Here is the Assignment Template:

[Note:To complete this template, replace the bracketed text with your own content. Remove this note before you submit your outline.]

Report:Selling Price and Area Analysis forD.M. Pan National Real Estate Company

Introduction

[Include in this section a brief overview, including the purpose of the report.]

Representative Data Sample

[Present your simple random sample of 30, including the region you selected for your sample. Then identify the mean, median, and standard deviation of the listing price and the square foot variables.]

Data Analysis

[Discuss how the regional sample created is reflective of the national market. Compare and contrast your regional sample with the national 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.]

Scatterplot

[Insert a scatterplot graph of the sample using the x and y variables noted earlier. Include a trend line and regression equation.]

The Pattern

[Based on your graph, define each variable, and explain which variable will be useful for making predictions and why.]

[Describe the association between x and y in the scatterplot and determine its shape. Identify any outliers you see in the graph and explain why these occur and what they represent.]

[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? Explain.]

Regression Equation

[Insert the regression equation for the line of best fit using the scatterplot you created.]

Determine r

[Determine r and what it means, including determining the strength of the correlation and discussing how you determine the direction of the association between the two variables.]

Examine the Slope and Intercepts

[Draw conclusions from the slope and intercept in the context of this problem and determine the value of only the land.]

R-squared Coefficient

[Explain what R-squared means in the context of this analysis.]

Conclusions

[Reflect on the relationship between square feet and sales price by addressing key considerations such as the comparison between your selected region and overall homes in the United States, as well as analyzing how the slope can help identify price changes, how the regression equation can help identify appropriate listing prices, and what square footage ranges the graph would be best used for.]

Here are the National Statistics (the website won't allow me to upload photos, so I unfortunately can't show you the graphs):

	n	Mean	Median	Std. Dev.	Min	Q1	Q3	Max
Listing price ($)	1,000	342,365	318,000	125,914	135,300	265,250	381,600	987,600
Cost per square foot ($)	1,000	169	166	41	71	139	191	344
Square feet	1,000	2,111	1,881	921	1,101	1,626	2,215	6,516

Here is the Excel graph with the region I chose:

Real Estate County Data for 2019
2019 Data (n=1000)
Region	State	County	listing price	$'s per square foot	square feet
East North Central	in	grant	219,500	$116	1,898
East North Central	il	vermilion	254,500	$156	1,632
East North Central	in	henry	235,000	$148	1,588
East North Central	in	wayne	203,800	$141	1,441
East North Central	il	coles	220,800	$117	1,893
East North Central	il	macoupin	197,600	$111	1,783
East North Central	in	vigo	165,800	$122	1,362
East North Central	oh	jefferson	246,500	$136	1,814
East North Central	il	jackson	154,300	$105	1,463
East North Central	oh	marion	149,700	$116	1,296
East North Central	mi	bay	145,100	$117	1,239
East North Central	il	whiteside	283,700	$136	2,087
East North Central	oh	trumbull	243,000	$133	1,827
East North Central	in	madison	229,100	$187	1,224
East North Central	il	knox	205,100	$118	1,740
East North Central	il	stephenson	235,600	$140	1,682
East North Central	il	macon	212,900	$128	1,659
East North Central	in	delaware	221,600	$134	1,651
East North Central	il	henry	257,700	$123	2,087
East North Central	oh	seneca	211,900	$168	1,263
East North Central	oh	darke	160,800	$114	1,416
East North Central	oh	scioto	204,200	$131	1,562
East North Central	oh	belmont	172,500	$101	1,710
East North Central	oh	sandusky	253,900	$146	1,738
East North Central	il	rock island	166,300	$127	1,305
East North Central	oh	clark	240,500	$137	1,752
East North Central	oh	columbiana	241,400	$164	1,469
East North Central	in	howard	304,300	$152	1,996
East North Central	oh	richland	248,900	$132	1,880
East North Central	il	peoria	187,900	$131	1,434
East North Central	il	la salle	311,100	$154	2,015
East North Central	il	madison	254,500	$156	1,628
East North Central	mi	wayne	213,800	$172	1,243
East North Central	in	vanderburgh	214,100	$134	1,596
East North Central	oh	mahoning	207,500	$123	1,688
East North Central	il	williamson	171,600	$141	1,218
East North Central	il	winnebago	236,700	$140	1,692
East North Central	il	adams	266,100	$166	1,599
East North Central	mi	saginaw	171,800	$118	1,452
East North Central	oh	montgomery	225,300	$151	1,493
East North Central	oh	allen	227,600	$147	1,550
East North Central	oh	lucas	228,300	$115	1,978
East North Central	oh	ashtabula	177,000	$107	1,658
East North Central	oh	lawrence	248,300	$156	1,587
East North Central	oh	huron	199,700	$147	1,359
East North Central	il	tazewell	278,700	$165	1,693
East North Central	oh	summit	185,800	$101	1,847
East North Central	il	sangamon	213,500	$130	1,643
East North Central	oh	ashland	188,000	$151	1,246
East North Central	oh	tuscarawas	270,700	$149	1,815
East North Central	oh	ross	257,200	$127	2,018
East North Central	mi	shiawassee	192,400	$129	1,494
East North Central	mi	calhoun	266,200	$130	2,042
East North Central	il	kankakee	148,700	$115	1,293
East North Central	in	lawrence	270,600	$137	1,978
East North Central	wi	manitowoc	181,400	$140	1,294
East North Central	il	st. clair	201,400	$164	1,225
East North Central	mi	ingham	222,500	$125	1,777
East North Central	il	mclean	203,800	$134	1,526
East North Central	mi	jackson	139,200	$116	1,201
East North Central	mi	isabella	163,000	$125	1,307
East North Central	wi	wood	266,500	$144	1,853
East North Central	mi	montcalm	218,300	$105	2,081
East North Central	wi	grant	243,200	$121	2,014
East North Central	oh	cuyahoga	265,100	$136	1,947
East North Central	oh	stark	201,000	$163	1,230
East North Central	oh	athens	246,400	$158	1,560
East North Central	wi	milwaukee	184,900	$111	1,666
East North Central	mi	lenawee	191,500	$118	1,628
East North Central	wi	fond du lac	135,300	$103	1,312
East North Central	in	st. joseph	193,000	$111	1,736
East North Central	mi	ionia	193,600	$137	1,416
East North Central	mi	genesee	194,800	$166	1,173
East North Central	oh	muskingum	188,300	$94	1,999
East North Central	il	ogle	236,600	$208	1,138
East North Central	oh	washington	324,400	$156	2,081
East North Central	oh	wayne	256,700	$129	1,986
East North Central	mi	muskegon	230,400	$131	1,757
East North Central	oh	pickaway	265,700	$143	1,853
East North Central	mi	st. joseph	188,500	$135	1,397
East North Central	il	champaign	246,700	$121	2,031
East North Central	oh	knox	192,200	$127	1,510
East North Central	oh	lorain	226,200	$126	1,789
East North Central	wi	calumet	226,400	$111	2,033
East North Central	mi	midland	174,500	$151	1,157
East North Central	mi	marquette	172,500	$120	1,433
East North Central	in	elkhart	202,300	$182	1,113
East North Central	mi	monroe	228,600	$136	1,679
East North Central	oh	lake	225,900	$135	1,676
East North Central	mi	eaton	189,900	$96	1,976
East North Central	wi	douglas	461,400	$129	3,581
East North Central	wi	marathon	431,200	$119	3,638
East North Central	il	dekalb	347,500	$97	3,574
East North Central	in	marion	323,300	$95	3,408
East North Central	in	allen	398,000	$113	3,525
East North Central	oh	hancock	380,300	$94	4,028
East North Central	in	lake	470,600	$109	4,316
East North Central	wi	portage	531,000	$109	4,888
East North Central	wi	rock	513,100	$104	4,950
East North Central	oh	greene	581,800	$113	5,146