(a) Assuming that a simple linear regression model is appropriate, estimate the regression model relating BOD (y) to the time (x).Round your final answers to 4 decimal places.What is the estimate of ô??Round your final answer to 3 decimal places.a = i(b) What is the estimate of expected BOD level when the time is 11 days?Round your final answer to 3 decimal places.(c) What change in mean BOD is expected when the time increases by 4 days?Round your final answer to 4 decimal places.(d) Suppose the time used is 8 days. Calculate the fitted value of y and the corresponding residual.Round your final answers to 4 decimal places.e-i(e) The following is a graph of ŷ versus the corresponding observed values yi.Scatterplot of fitted vs BOD454.0353.0-2520151.00.51.01.52.02.53035BODWhich of the following describes what this plot would look like if the relationship between y and xwas a deterministic (no randomerror) straight line?O the nnints would all be eoualfitted An article in the Journal of the Environmental Engineering Division ("Least Squares Estimates of BOD Parameters," Vol. 106, 1980, pp.1197-1202) describes the results of testing a sample from the Holston River below Kingport, TN, during August 1977. Thebiochemical oxygen demand (BOD) test is conducted over a period of time in days. The resulting data is shown below:Time (days) BOD (mg/liter)1.0.620.71.51.982.1102.6122.9143.7163.5183.7203.8Minitab output resulting from fitting a simple linear regression model with time as the explanatory variable and BOD as the responsefollows.PredictorCoefSE CoefPConstant0.65780.16573.970.003Time0.178060.0140012.720.000s-0.287281 R-Sq - 94.7% R-Sq(adj) – 94.1%Analysis of VarianceSourceDFSSMSFPRegression13.34413.344161.690.000Residual90.7430.083ErrorTotal1014.0874.

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MATLAB: An Introduction with Applications

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Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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The Toyota Camry is one of the best-selling cars in North America. The cost of a previously owned Camry depends upon many factors, including the model year, mileage, and condition. To investigate the relationship between the car's mileage and the sales price for a 2007 model year Camry, the following data show the mileage and sale price for 19 sales (PriceHub website). Click on the datafile logo to reference the data. DATA file 1. 18 Price ($1000s) 16 14 12 10 18 6 If your answer is zero, enter "0". a. Select a scatter diagram with the car mileage on the horizontal axis and the price on the vertical axis. 20 40 6,0 8,0 100 Miles (1000s) 120 223 +♡ ♡ Miles(1000s) 29 36 47 63 77 73 87 92 101 110 28 59 68 68 91 42 65 110 Price ($1000s) 16.2 16.0 13.8 11.5 12.5 12.9 11.2 13.0 11.8 10.8 8.3 12.5 11.1 15.0 12.2 13.0 15.6 12.7 8.3
Consider a linear regression model for the decrease in blood pressure (mmHg) over a four-week period with muy=2.8+0.8x and standard deviation chi=3.2. The explanatory variable x is the number of servings fruits and vegetables in a calorie-controlled diet. Explain clearly what this slope says about the change in the mean of y for a change in x.
Select the appropriate interpretation for the slope of the linear regression equation below. Y (Dependent Variable) = Grade Point Average X (Independent Variable) = Average number of hours spent using electronic devices for entertainment purposes yhat = 4 - 0.125*X A. For every 1 hour more spent using electronic devices for entertainment per week then a person's GPA will increase on average by 0.125 points B. For every 1 GPA gained obtained by a student then on average that person will have watched 0.125 hours fewer of entertainment on electronic devices per week C. For every 1 GPA point lost by a student then on average that person will have watched 0.125 hours more of entertainment on electronic devices per week D. For every 1 hour more spent using electronic devices for entertainment per week then a person's GPA will decrease on average by 0.125 points
A regression coefficient is given Match the correct equation with answers given below Y =0.00114x + 2.53 Y=1.662x + 83.34 Y = -1.04x + 50.3 Y= -0.667x + 52.6
The following table shows both current and projected data on the number, in millions, of Facebook users in a certain country. t = years since 2012 F = number of Facebookusers (millions) 0 9.7 1 10.5 2 10.8 3 12.2 4 13.1 5 13.2 6 13.8 (a) Plot the data. (b) Find the equation of the regression line. (Round regression line parameters to two decimal places.) F(t) = Add the graph of the regression line to the plot from part (a). (c) Explain in practical terms the meaning of the slope of the regression line. (Round your answers to two decimal places). The slope of the regression line is million users per year. The slope means that, from 2012 on, the number of Facebook users in the country is expected to increase by million each year.
From the results shown above, write the regression equation.
The next four questions (29 to 32) refer to the following: To most Canadians, earthquakes are viewed as rare occurrences, but they are actually quite common. In just one month in 2001, Natural Resources Canada recorded 215 earthquakes that affected Canada from B.C. to Nunavut to Newfoundland. We would like to determine whether there is a linear relationship between the location of an earth- quake X (measured in degrees latitude north of the equator) and the magnitude of the earthquake Y (measured on the Richter scale). The explanatory and response variables are measured for a sample of 13 earthquakes. The equation of the least squares regression line is ŷ = -3.05+ 0.10x. The ANOVA table is showm below: ге Source of Variation df Sum of Squares Mean Square F Regression Error Total 1.40 25.10

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