Hello, this is a Applied Marketing Strategies question for Real Estate Analysis. If you can please help answer questions #1 - 3 using the attached picture and given information.Some of the questions have been worked already. Thank you!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.Generate a Representative Sample of the DataSelect a region and generate a simple random sample of 30 from the data.(shown in attached picture)Report the mean, median, and standard deviation of the listing price and the square foot variables.(shown in attached picture)Analyze Your Sample1. Discuss how the regional sample created is or is not reflective of the national market.2. Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data:Summary Statistics for Real Estate Data(shown in picture)nMeanMedianStd. Dev.MinQ1Q3MaxListing price ($)1,000342,365318,000125,914135,300265,250381,600987,600Cost per square foot (S)1,000169166?71139191344Square feet1,0002,1111,8819211,1011,6262,2156,516This graph shows the frequency for listing price.National Listing Prices (Ss)Frequeney300200-100120000040000?600003listing priceThis graph shows the frequency for square feet.National Listing's Square Feet80MH0100000200-4000)square feetS00060007000Explain how you have made sure that the sample is random.Explain your methods to get a truly random sample.Generate ScatterplotCreate a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes.Observe patterns3. 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?

$'s per Region State County listing price square foot square feet random Mountain co douglas 387,000 $162 2,383 0.2378488 sample national Mountain broomfield 292,800 $146 2,005 0.9809432 mean price $406, 193 342,365 Mountain lea 394,500 $186 2,125 0.781293 median price $364,900 318,000 Mountain carson city 396,700 $205 1,936 0.7399622 std dev price 122392 125,914 Mountain jefferson 354,800 $156 2,274 0.1382713 Mountain d bannock 367,600 $206 1,781 0.2764659 Mountain clark 274, 100 $193 1,419 0.9405646 sample national Mountain nt gallatin 348,800 $244 1,431 0.6806107 mean price 2,407 2,111 Mountain el paso 539,600 $126 4,273 0.9885838 median price 2,018 1,88 Mountain az navajo 358,200 $222 1,611 0.2194719 std dev price 1108 921 Mountain a2 pima 359,300 $203 1,768 0.0188394 Mountain az cochise 381,000 $189 2,018 0.5590683 Mountain garfield 748, 100 $129 5,817 0.0404427 Mountain CO garfield 364,900 $167 2, 186 0.4847819 Chart Title y = 104.33x + 155102 Mountain d ada 315,500 $142 2,222 0.4027178 200,0 00 Mountain im mckinley 731,500 $143 5,099 0.8578965 300,0 00 Mountain pima 393,900 $225 1,751 0.91 18825 Mountain a> yavapai 389,700 $169 2,300 0.2839722 700,000 Mountain curry 307,900 $158 1,953 0.9350197 Mountain mt cascade 309,800 $194 1,598 0.4075556 800,0 00 Mountain mesa 308,200 $163 1,890 0.485384 500,0 00 Mountain nt missoula 310, 100 $196 1,586 0.6374169 Mountain az navajo 339.000 $177 1,916 0.4909703 100,0 00 Mountain nm eddy 599,300 $165 3,636 0.203725 Mountain otero 468,500 $211 2,220 0.9070765 300,0 00 Mountain eagle 361,600 178 2,035 0.1329424 200,0 0 Mountain pinal 314,800 $223 1,413 0.2245505 Mountain curry 528,000 $142 3,720 0.9272406 100,0 0 Mountain nm dona ana 534,400 $156 3,431 0.8800192 1,000 2,000 3,000 4,000 5,000 6,000 7,000 square foot ($) Square 1,000 2,11 1 1,881 921 1,101 1,626 2,215 6,516 feet This graph shows the frequency for listing price. National Listing Prices (Ss) 300 200 100 200000 400000 600000 800040 1090800 listing price