1. In the Real Estate data example, we predicted Prices using one or more independent variables. If you were conducting Simple Linear Regression, using Distance to the Nearest MRT Station as the independent variable, what would the R squared value be?
2. If the correlation coefficient between House Age and House Price is -0.210567. Without doing a regression analysis, state the R squared value of the simple linear regression between House Age and House Price.
3.
Consider the following multiple regression equation:
Price = 42.977 - 0.253*House Age - 0.005*Distance + 1.297*Number of Convenience Stores
What will be price of the house if the age of the house is 47, the distance from the nearest MRT station is 2000 and the number of convenience stores around the house are 5.
4. In the multiple regression above, there were three independent variables. Based on that, what will be the regression degrees of freedom? Are there any variables in that analysis that are not statistically significant?
Homework Answers
1.
R sqaure = 0.06113
2. Rsquare= r^2 = 0.044338
3. The predicted price for given set of values is 26.571
4. The regression degree of freedom is always equal to number of explanatory variables involved in fitting of the equation. Thus for multiple regression above df are 3.
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1. In the Real Estate data example, we predicted Prices using
one or more independent variables....
A real estate company wants to study the relationship between house sales prices and some important...
A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the area, the variables y= sales price (in thousands of dollars) * " total floor area (in square feet) * number of bedrooms X; - distance to nearest high school (in miles) are used in a multiple regression model. The estimated model is 9 - 79+0,065x + 25x2 - 7*3 Answer the...
A real estate company wants to study the relationship between house sales prices and some important...
A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the area, the variables y - sales price (in thousands of dollars) Xy - total floor area (in square feet) = number of bedrooms *; - distance to nearest high school (in miles) are used in a multiple regression model. The estimated modelis 9 – 188+0.073x, +21x2 - 6x3 50 00 Answer...
Assignment 2 PART 1. 1. Use the dataset below to run a regression where x1 and...
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1. Refer to the Class Commute Data, and let the independent variable Distance (between home and s...
1. Refer to the Class Commute Data, and let the independent variable Distance (between home and school) and the dependent variable Leave (one-way commute time to school). Using matrix method and the selected variables from the Class Data, obtain the following for an OLS simple linear regression model: Matrices Y, X and ß a. ons developed by the method of least squares c. Get B from (b), and write the fitted regression line. Return Home Leave Home to From Schoo...
please help thank you! Selling Information For Real Estate Value Price SqFt Brick (1 if brick,...
please help thank you!
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1. In simple linear regression analysis, we assume that the variance of the independent variable (X) is equal to the variance of the dependent variable (Y) True False 2. The standard deviation of the sampling distribution of the sample mean is the same as the population standard deviation. True False 3. If n=20 and p=.4, then the mean of the binomial distribution is 8 True False 4. If a population is known to be normally distributed, then it follows that...
A B С D E F G H 1 WinterRain HarvestRain 160 Age 31 2 600...
A B С D E F G H 1 WinterRain HarvestRain 160 Age 31 2 600 3 690 80 4. 502 130 Year 1952 1953 1955 1957 1958 1959 1960 5 420 110 187 30 28 26 25 24 23 6 7 582 485 763 830 8 9 1961 22 10 1962 697 21 20 11 12 1963 1964 608 402 19 13 602 18 Price 7.495 8.0393 7.6858 6.9845 6.7772 8.0757 6.5188 8.4937 7.388 6.7127 7.3094 6.2518 7.7443 6.8398...
4. (24 marks) Suppose that the random variables Yi,..., Yn satisfy Y-B BX,+ Ei, 1-1, , n, where βο and βι are parameters, X1, ,X, are con- stants, and e1,... ,en are independent and identically distr...
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a) Construct a regression model using all four independent variables. (Round to three decimal places as...
a) Construct a regression model using all four independent
variables. (Round to three decimal places as needed.)
b) Identify the general form of the null and alternative
hypotheses.
c) Find the test statistic for the coefficient of each
independent variable. (Round to two decimal places as needed.)
d) Determine the appropriate critical value(s) for α=0.10.
(Round to three decimal places as needed.)
e) Find the p-value for the coefficient of each independent
variable. (Round to three decimal places as needed.)...
1.Which variables are statistically significant at the 5% level? 2.Which variables are statistically significant at the...
1.Which variables are statistically significant at the 5%
level?
2.Which variables are statistically significant at the 10%
level?
3.Which variables are insignificant?
4.Please present the correlation matrix of the independent
variables.
5.Please run the White test for heteroskedasticity, with
cross-products AND PRESENT YOUR RESULTS. Please explain whether the
test is significant or not.
6.If the White test is significant, please present the
heteroskedasticity-consistent White regression results.
7.Can you test this model for autocorrelation? Why of why not?
If you do,...
A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the area, the variables y= sales price (in thousands of dollars) * " total floor area (in square feet) * number of bedrooms X; - distance to nearest high school (in miles) are used in a multiple regression model. The estimated model is 9 - 79+0,065x + 25x2 - 7*3 Answer the...
A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the area, the variables y - sales price (in thousands of dollars) Xy - total floor area (in square feet) = number of bedrooms *; - distance to nearest high school (in miles) are used in a multiple regression model. The estimated modelis 9 – 188+0.073x, +21x2 - 6x3 50 00 Answer...
1. Refer to the Class Commute Data, and let the independent variable Distance (between home and school) and the dependent variable Leave (one-way commute time to school). Using matrix method and the selected variables from the Class Data, obtain the following for an OLS simple linear regression model: Matrices Y, X and ß a. ons developed by the method of least squares c. Get B from (b), and write the fitted regression line. Return Home Leave Home to From Schoo...
please help thank you!
Selling Information For Real Estate Value Price SqFt Brick (1 if brick, if othewise) $241,255 3,392 0 $184,518 2,038 1 $176,488 1,906 0 $240,068 3,329 0 $169,760 1,828 0 $185,335 2,081 0 $172,735 1, 9260 $224,281 3,4250 $172,589 1,676 1 $214,635 2,735 1 $199,666 2,373 1 $208,348 2,662 1 $218,360 2, 8341 $230,160 3, 2540 $164,812 1,431 0 $191,560 1,839 1 $203,255 2, 4561 $173,325 1,530 $168,073 1.381 1 $179,620 1,4571 TABLE 4 Industrial CEO Salary...
A B С D E F G H 1 WinterRain HarvestRain 160 Age 31 2 600 3 690 80 4. 502 130 Year 1952 1953 1955 1957 1958 1959 1960 5 420 110 187 30 28 26 25 24 23 6 7 582 485 763 830 8 9 1961 22 10 1962 697 21 20 11 12 1963 1964 608 402 19 13 602 18 Price 7.495 8.0393 7.6858 6.9845 6.7772 8.0757 6.5188 8.4937 7.388 6.7127 7.3094 6.2518 7.7443 6.8398...
4. (24 marks) Suppose that the random variables Yi,..., Yn satisfy Y-B BX,+ Ei, 1-1, , n, where βο and βι are parameters, X1, ,X, are con- stants, and e1,... ,en are independent and identically distributed ran- dom variables with Ei ~ N (0,02), where σ2 is a third unknown pa- rameter. This is the familiar form for a simple linear regression model, where the parameters A, β, and σ2 explain the relationship between a dependent (or response) variable Y...
a) Construct a regression model using all four independent
variables. (Round to three decimal places as needed.)
b) Identify the general form of the null and alternative
hypotheses.
c) Find the test statistic for the coefficient of each
independent variable. (Round to two decimal places as needed.)
d) Determine the appropriate critical value(s) for α=0.10.
(Round to three decimal places as needed.)
e) Find the p-value for the coefficient of each independent
variable. (Round to three decimal places as needed.)...
1.Which variables are statistically significant at the 5%
level?
2.Which variables are statistically significant at the 10%
level?
3.Which variables are insignificant?
4.Please present the correlation matrix of the independent
variables.
5.Please run the White test for heteroskedasticity, with
cross-products AND PRESENT YOUR RESULTS. Please explain whether the
test is significant or not.
6.If the White test is significant, please present the
heteroskedasticity-consistent White regression results.
7.Can you test this model for autocorrelation? Why of why not?
If you do,...
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