The solution must be displayed in excel and -4 maths in a separate sheet. Please last time Unifolks...

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The solution must be displayed in excel and -4 maths in a separate sheet. Please last time Unifolks gave me the wrong answer I lost 10 marks.

Problem 1 Problem 1 Compute sample correlation coeeficient and the coefficients for the least-squares regression line Given the following dataWe want to predict the selling price of a house in Newburg Park FL based on the distance the house lies from the beach. Distance from the beach, x (in miles)Selling price, y (in thousands of dollars) 6.2302.7 18.5216.3 8.5250 8.3292.3 4.1308.5 4.9264.8 11.6227 13.8265.5 13.5196.6 13.2188 10274.4 7.4234.3 6.2270.8 5.7216.4 10.9197.3 9.2290.2 What is the value of the slope What is the value of the y-intercept NOTE: Round answers to three decimal laces Problem 2 Problem 2 Explained and unexplained variation and the least-squares regression line Given the following data: xy 107.4125.7 122.1131.9 127.4123.1 137145.6 147.7141.6 What is the equation for this sample? What is the variation in the sample y values that is not explained by the estimated linear relationship (SSE)? What is the proportion of the toal variation in the sample y values that is explained by the estimated linear relationship (r-squared)? For the data point (107.4,125.7) what is the residual? Problem 3 Problem 3 Linear relationship and the sample correlation coefficient Given the following four data sets and scatter plots. xyuv 13.4110 25.829 38.238 49.247 59.556 610.165 79.274 87.883 96.392 104.1101 wtmn 17.613 2924.1 37.333.6 45.645.3 58.455 64.767.2 7576.3 86.787.8 95.997.2 103.9107.9 Answer the following questions: (by giving the 2 variables or the answer None) Which data set is there evidence of a strong nonlinear relationship between 2 variables? Which data set indicates the strongest negatibe linear relationship between 2 variables? Which data set has an apparent positive, but not perfect, linear relationship between 2 variables? Which data set indicates a perfect positive linear relationship between 2 variables? 123456789103.45.88.19999999999999939.19999999999999939.510.19.19999999999999937.86.34.09999999999999961234567891010987654321123456789107.697.35.68.44.756.75.93.91234567891034.09999999999999963.65.357.26.37.87.27.9 Problem 4 Problem 4 Regression 2 Independent Variables Predicting job performance of auto mechanics based on mechanical aptitude test scores and personality testing that measures conscientiousness. Given the following data Y = job performance X1 = mechanical aptitude scores X2 = persomality test/conscientiousness measure YX1X2 114025 224520 313830 435030 524828 635530 735334 845536 945832 1034034 1155538 1234828 1334530 1425536 1546034 1656038 1756042 1856538 1945034 2035838 What is the regression equation with the 2 idependent variables (x1, x2)? What is the correlation coefficient?

quiz2regression-tfrvurfg.xlsx

Monica · Accepted Answer

Problem 1
	Problem 1
		Compute sample correlation coeeficient and the coefficients for the least-squares regression line
		Given the following data		We want to predict the selling price of a house in Newburg Park FL
				based on the distance the house lies from the beach.
		Distance from the beach, x (in miles)	Selling price, y (in thousands of dollars)
		6.2	302.7
		18.5	216.3
		8.5	250
		8.3	292.3
		4.1	308.5
		4.9	264.8
		11.6	227
		13.8	265.5
		13.5	196.6
		13.2	188
		10	274.4
		7.4	234.3
		6.2	270.8
		5.7	216.4
		10.9	197.3
		9.2	290.2
		What is the value of the slope
		What is the value of the y-intercept
		NOTE: Round answers to three decimal laces
Solution_1
			Distance from the beach, x (in miles)	Selling price, y (in thousands of dollars)
			6.2	302.7
			18.5	216.3
			8.5	250
			8.3	292.3
			4.1	308.5
			4.9	264.8
			11.6	227
			13.8	265.5
			13.5	196.6
			13.2	188
			10	274.4
			7.4	234.3
			6.2	270.8
			5.7	216.4
			10.9	197.3
			9.2	290.2
	Solution 
		1)	Slope	-5.749
		2)	Intercept	304.313
			Slope and intercept are the coefficient of the least square regression line equation
solution_2
	SUMMARY OUTPUT
	Regression Statistics
	Multiple R	0.75
	R Square	0.56
	Adjusted R Square	0.41
	Standard Error	7.54
	Observations	5
	ANOVA
		df	SS	MS	F	Significance F
	Regression	1	213.08	213.08	3.75	0.15
	Residual	3	170.47	56.82
	Total	4	383.55
		Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
	Intercept	72.10	31.93	2.26	0.11	-29.52	173.71	-29.52	173.71
	x	0.48	0.25	1.94	0.15	-0.31	1.27	-0.31	1.27
	Solution 
	1)	  True, the variation in the sample y values that is not explained by the estimated linear regression.  From the above table we can observed that sum of square error value is equal to 170.47 
	2)	    The proportion of the total variation in the sample y values that is explained by the estimated linear relationship.

Problem 1 Problem 1 Compute sample correlation coeeficient and the coefficients for the least-squares regression line Given the following data We want to predict the selling price of a house in...

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