HW 10 Question 7: Suppose you are interested in the relationship between the square footage of a house and the market value. Which of the following statements are true (select all that apply)? A The x-variable would be the square footage B The y-variable would be the square footage C The dependent variable would be the square footage D The independent variable would be the square footage E The response variable would be the square footage F The explanatory variable would be the square footage G The x-variable would be the market value H The y-variable would be the market value I The dependent variable would be the market value J The independent variable would be the market value K The response variable would be the market value L The explanatory variable would be the market value
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In such a relationship, we typically assume that the square footage *influences* or *explains* the market value. Show more…
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One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and asking price​ (in thousands of​ dollars) for a random sample of homes for sale. Complete parts​ (a) through​ (h). ​(a) Which variable is the explanatory​ variable? A. Determining the value of a home B. Asking price C. Number of homes D. Square footage
Ivan K.
biggest factors determining the value. Complete parts (a) through (h) below. Find the least-square regression line using square footage as the explanatory variable. Data Table: Square Footage: 2183, 3234, 3811, 1868, 3429, 6137, 3616, 6361, 3853, 3061, 2720, 2264, 2724, 1671 Selling Price ($000s): 381.8, 186.8, 342.9, 613.7, 361.6, 636.1, 385.3, 292.4, 257.5, 707.9, 392.4 Interpret the slope: Select the correct choice below and fill in the answer box to complete your choice. For every additional thousand dollars, the selling price of square footage increases by (Round to decimal places as needed). For every additional square foot, the selling price increases by (Round to decimal places as needed) thousand dollars. It is not appropriate to interpret the slope. Interpret the y-intercept: Why? Select the correct choice below and fill in the answer box to complete your choice. A house of 0 square feet is possible and within the scope of the model. (Type an integer or a simplified fraction) A house of 0 square feet is not possible and outside the scope of the model. (Type an integer or a simplified fraction) A house of 0 square feet is outside the scope of the model.
Umar Sohail Q.
A real estate expert wanted to find the relationship between the sale price of houses and various characteristics of the houses. She collected data on five variables for 25 houses that were sold recently. Dependent variable is the sale price of the house (in 1000 TL). Independent variable X1 refers to size of the house in sq.meters, X2 refers to size of the living area in sq.meters, X3 refers to age of the house in years, X4 refers to number of rooms in the house, and X5 refers to whether the house has a private garage (X5 = 1 if the answer is yes, X5 = 0 if the answer is no). The following regression output (with some values missing, you have to fill them as much as you can) was presented to the real estate expert: Regression Statistics Multiple R 0.907 R Square Adjusted R Square Standard Error Observations 25 ANOVA SS df MS F p-value Regression 417 Residual/Error 89 Total 506 Coefficients Standard Error t stat p-value Intercept 200.15 5.6128 X1 11.90 0.456 X2 0.10 0.087 X3 -7.55 0.239 X4 19.00 10.00 X5 8.50 0.042 The following correlation matrix was developed. Based on this, which variable(s) indicate(s) a multicollinearity problem? X1 X2 X3 X4 X5 X1 1 X2 -0.539 1 X3 -0.953 0.885 1 X4 0.008 0.235 0.930 1 X5 0.252 0.456 -0.860 0.332 1 Select one: a. X4 b. X2 c. X3 d. X2 and X3 e. X2, X3, and X5 f. X5 g. X1 h. X3 and X4 i. X1 and X3
Aishwarya K.
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