44.537.938.936.945.8(a) Calculate the least squares estimates of the slope and intercept.iBo =(b) Find the mean selling price given that the taxes paid are x - 7.7.i(Round your answer to 2 decimal places.)(c) Calculate the fitted value of y corresponding to x - 5.3003 (observation #10). Find the corresponding residual.y = i(Round your answer to 2 decimal places.)y - y =8.79516.08318.36078.14009.1416(Round your answer to 3 decimal places.)(Round your answer to 2 decimal places.)(Round your answer to 2 decimal places.) Please use the accompanying Excel data set or accompanying Text file data set when completing the following exercise.An article in Technometrics by S. C. Narula and J. F. Wellington ("Prediction, Linear Regression, and a Minimum Sum of Relative Errors,"Vol. 19, 1977) presents data on the selling price (y) and annual taxes (x) for 24 houses. The taxes include local, school and county taxes.The data are shown in the following table.Sale Price/1000 Taxes/100025.94.917629.55.020827.94.542925.94.557329.95.059729.93.891030.95.898028.95.603935.95.828231.55.300331.06.271230.95.959230.05.050036.98.246441.96.696940.57.784143.99.038437.55.989437.97.542244.58.795137.96.083138.98.3607

Regression equation used to predict the variable over a period of time. It has two variable they are…

Answered: Please use the accompanying Excel data…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The table shows the national expenditures for health care in billions, in a country for the selected years from 1990 to 2020. Given the projection cost for the year 2002, identify the type of regression point. Year Exprenditures ($billions) 1991 1020 1994 1356 1998 1984 2004 2984 2009 3374 2016 4765 2020 5937 Interpolation Extrapolation Neither Both
2. Following data is amount of Assessed Value for an office building for a given floor area, number of office space, number of entrances, and the age of the offic building. Use excel to …. Obtain a Scatter plot of Floor Area as the independent and Assessed value as the dependent variable. Note the linear regression Model Predict the assessed value for 6000 sq ft. FloorArea (Sq.Ft.) Offices Entrances Age AssessedValue ($'000) 4790 4 2 8 1796 4720 3 2 12 1544 5940 4 2 2 2094 5720 4 2 34 1968 3660 3 2 38 1567 5000 4 2 31 1878 2990 2 1 19 949 2610 2 1 48 910 5650 4 2 42 1774 3570 2 1 4 1187 2930 3 2 15 1113 1280 2 1 31 671 4880 3 2 42 1678 1620 1 2 35 710 1820 2 1 17 678 4530 2 2 5 1585 2570 2 1 13 842 4690 2 2 45 1539 1280 1 1 45 433…
The following chart shows the actual sales for the last 12 months for a given company. Assume that sales are best fit by a linear trend and you can use single linear regression to set up a forecasting model. Using the sales data answer below questions (justify your answers): A.What would be the typical linear regression equation for the number of sales? B.Make the sales forecast for period 15 of next year. C. Make the sales forecast for period 17 of next year. D. What is the standard error for the data?
The basic hypothesis is that people who play sports are more likely than others to watch sport on TV. Your first task is to crosstabulate the data involving the playing and watching of sports and to determine the direction and strength of that relationship. Write out your findings about this basic relationship. Your next task is to determine the direction and strength of the partial relationships when you control for the gender of individuals.
Plot 1 Out-of-State Tuition Plot 1: Out-of-State Tuition vs Student-Faculty Ratio 20000 15000 10000 5000 10 20 Student-Faculty Ratio 30 40 Expenditure Category • Above Average Expenditure • Below Average Expenditure
A. Interpret the slope of coefficient . B. Interpret the value of coefficient of determination . c. Using the decision rule based on (-statistic, test at the 10% significatice level whether or not there is a linear relationship between advertising expenditure and sales. In other words, test the following hypotheses: H0 : B1 = 0 (there is no relationship) H1 : B1 ≠ 0 (there is a relationship)
a) Determine the correlation coefficient, r, and interpret this value in the context of the problem. (Round 4 decimal places)b) Find the equation of the regression line for the given data. (Round the slope and y-intercept 4 decimal places).c) Give a practical interpretation of the slope of the regression line.
The purpose of this assignment is to apply simple regression techniques to find factors that determine the car values. AS Instructions: 1. Open the dataset of FamilySedans (attached) and read the case entitled “Finding the Best Car Value” in its entirety at the end of Chapter 14. 2. Use descriptive statistics to summarize the data and make comments on them. 3. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the price of the car. 4. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the five-year owner costs. 5. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the road-test score. 6. Use regression analysis to develop an estimated regression equation that could be used to predict the value score given the predicted-reliability. 7. What conclusions can you derive from your…

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