Notice: There are six (6) questions. Poetical LLC, an international business con
ID: 3172774 • Letter: N
Question
Notice: There are six (6) questions. Poetical LLC, an international business consulting firm, is opening an office in Beijing, China. Data was gathered from 31 "5A" office buildings near Beijing's Financial Street and a simple regression was run to predict the monthly rent cost based on the square footage of the office space. The rents in the sample range from $15, 500 to $32,000 and the office sizes in the sample range from 740 to 1, 260 square feet. The output from the Excel regression is provided at the follwlng1. Write out the regression equation (with the calculated coefficient estimates). 2. Interpret the meaning of b_j (slope) in this problem. 3. What is this regression's coefficient of determination (r2) and what does it tell you about the model? 4. At the 0.05 level of significance, is there evidence of a linear relationship between the rent and square footage? Explain 5. You are considering signing a lease for an office of 1000 sq ft in the same neighborhood. The rent is $21, 975. Is this reasonable based on the prediction from the regression model? Why or why not? 6. You are considering signing a lease for a small office in the same neighborhood. The space is 350 sq ft. Can you use this model to predict the monthly rent for that apartment? Why or why not?Explanation / Answer
1. MonthtySquaerFootage = 25.0017*Size -2010.5068
2. It means that for 1 unit increase in size price increases by $25.0017*1000
3. r2 square is .67. It means that 67% of varinace in model is explained by Size
4.Yes. Check Significance F is less than .05. Check variable' significane, it s less than .05 which means that even variables is significant
5.Pricepred=25.0017*1000-2010.5068 = $22991. Since the given rent is 21975, the rent is less than predicted value of 22991, and hence is reasonable.
6. NO. We cannot. Model was created using higher range of linear regression
and not low values of size. Linear reg model may not be so accurate for such low values of size
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