1. Since the slope of given regression line is negative, greater values of x associated with lesser value of y.
The answer is Less than
2. Predicted decrease = Slope = 5.01
3. Predicted house price = 297.33 - 5.01*6.1 = 266.8
4. Observed house price = 303.5
With the aim of predicting the selling price of a house in Newburg Park, Florida, from...
With the aim of predicting the selling price of a house in Newburg Park based on the distance the house lies from the beach, we're examining data for houses sold in Newburg Park in the past year. These data detail the distance (x, in miles) of the house from the beach and the selling price (y, in thousands of dollars) of the house for each of 14 houses. The least-squares regression equation based on the data is y=302.76–4.99x. We're interested...
AND CORRELATION Computing the sample correlation coefficient and the coefficien. Chidera v We want to predict the selling price of a house in Newburg Park, Florida, based on the distance the house lies from the beach Suppose that were given the data in the table belon These data detail the distance from the beach (xin miles) and the selling pricely, in thousands of dollars) for each of a sample of sixteen homes sold in Newburg Park in the past year....
House Selling Price Data for 100 homes relating y = selling price (in dollars) to x = size of the house (in square feet) results in the regression line that is shown below. y= 9161 + 77.008x the slope estimate has standard error 6.262 Show all steps of a two-sided significance test of independence. Could the sample association between these two variables by explained by random variation? a) Assumptions b) Hypotheses: c) Test Statistics: d) p-value: e) Conclusion:
Suppose the following data were collected relating the selling price of a house to square footage and whether or not the house is made out of wood. Use statistical software to find the regression equation. Is there enough evidence to support the claim that on average wood houses are more expensive than other types of houses at the 0.01 level of significance? If yes, type the regression equation in the spaces provided with answers rounded to two decimal places. Else,...
The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of sixteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands...
Question 1 Suppose we wanted to predict the selling price of a house using its size in a certain area of a city. A random sample of six houses were selected from the area. The data is presented in the following table with size given in hundreds of square feet, and sale price in thousands of dollars. Size (Xi) 12 15 18 21 24 27 Price (Yi) 60 85 75 105 120 110 a) Find the least squares estimate for 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...
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 local realtor wishes to study the relationship between selling price (in $) and house size (in square feet). A sample of 10 homes is selected at random. The data is given below: PRICE HOUSESIZE 100000 1600 107000 1750 121000 1900 124000 2150 132000 2400 140000 2300 144000 2400 158000 2700 170000 3000 182000 2900 a) Find the regression equation relating Price to Square Footage. b) Calculate the correlation coefficient, accurate to three decimal places c) Test the significance of...
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...