The slope D of the sample regression line provides a measure ofO1.the change in the population value of the dependent variable for every unit change In the Independent varlable.O 2. the change in the population average value of the dependent varlable for overy unit change in the independent varlable,03.the change In the population value of the independent varlable for every unit change in the dependent varlable.04.the change in the population average value of the independent variable for every unit change in the dependent varlablo.O 5.the change in the estimated population value of the dependent variable for every unit change in the Independent varlable.O 6.the change in the estimated population average value of the dependent variable for every unit change in the independent varlable.O 7. the change in the estimated population value of the independent variable for every unit change in the dependent variable,O 8. the change in the estimated population average value of the independent varlable for every unit change in the dependent varlable,

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Answered: The slope b of the sample regression…

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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A. run a simple regression- dependent variable is Weeks, independent variable is Age. B. run a multiple regression with dependent variable weeks and independent variable-age, married, head, manager and sales. C. Create the regular and standardized residual plots for both. Please show the tables when entering values of the regression for both the outputs and the scatter plots.
+ + + + + 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 data a Find these values. Type DNE if the value cannot be determined from the boxplot: Min = Q₁ = Median Q3 Max = IQR = Range = a. Which quarter has the smallest spread of data? 1st 2nd 3rd 4th b. Which quarter has largest spread of data? 1st 2nd 3rd 4th c. What percentage of the data lies between 2 and 13? d. What percentage of the data lies between 13 and 14? % %
R5.30. Hard water In an investigation of environmental causes of disease, data were collected on the annual mortality rate (deaths per 100,000) for males in 61 large towns in England and Wales. In addition, the water hardness was recorded as the calcium concentration (parts per million, or ppm) in the drinking water. Here are the scatterplot and regression anal- ysis of the relationship between mortality and calcium concentration. Dependent variable is Mortality R-squared = 43% s = 143.0 with 61 - 2 = 59 degrees of freedom Variable Intercept Calcium Mortality (deaths/100,000) 2000 1800 1600 1400 1200+ Coefficient 1676 -3.23 30 SE(Coeff) 29.30 0.48 90 60 Calcium (ppm) 120 a) Is there an association between the hardness of the water and the mortality rate? Write the appropriate hypothesis. b) Assuming the assumptions for regression inference are met, what do you conclude? c) Create a 95% confidence interval for the slope of the true line relating calcium concentration and mortality. d)…
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 11 9 12 8 11 13 4 13 6. 6 У 7.25 7 12.94 7.22 8.15 9.27 6.33 5.3 8.52 6.14 5.46 Create a scatterplot of the data. Choose the correct graph below. O B. OC. O D. O A. Ay 25- Ay 25- 25- 25- 20- 20 20- 20 15 15 15 15 10 10 10- 10 5- 5- 5- 5- 0- 05 10 15 20 25 05 10 15 20 25 0- 05 10 15 20 25 0 5 10 15 20 25 Find the equation of the regression line. (Round the constant two decimal places as needed. Round the coefficient to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. O A. There is no trend in the data. O B. The data has a pattern that is not a straight line. C. There is an influential point that strongly affects the graph of the regression line. D. There is no characteristic of the data that is ignored by the regression line. Click to select your answer(s).…
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 9 9 11 10 11 14 4 13 7 6 y 7.59 6.87 13.06 7.32 8.58 6.09 5.62 8.35 6.73 7.77 5.9 Create a scatterplot of the data. Choose the correct graph below. O A. OB. OC. Oc. OD. Ay 25- Ay 25- Ay 25- 25- 20 20- 20- 20- 155 155 155 155 105 105 105 105 5- 55 55 55 0- Ó 5 10 15 20 25 0- 0- 05 10 15 20 25 Ó 5 10 15 20 25 0 5 10 15 20 25 Find the equation of the regression line. (Round the constant two decimal places as needed. Round the coefficient to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. O A. The data has a pattern that is not a straight line. O B. There is no characteristic of the data that is ignored by the regression line. OC. There is an influential point that strongly affects the graph of the regression line. O D. There is no trend in the data.
The OLS estimator is derived by A. making sure that the standard error of the regression equals the standard error of the coefficient estimator. B. minimizing the sum of squared regression. C. minimizing the sum of squared error. D. connecting the Y; corresponding to the lowest X; observation with the Y; corresponding to the highest X; observation. Decat Celoction O O
Use the regression line to estimate the number of trials it would take to learn these tricks if a dolphin received five treats per trick. Y for X = 5 would be _________.
5 prac
27. What percentage of the variability is accounted for by the regression model?A. 1% B. 2% C. 98% D. 99%28. Is there a linear relationship between the dependent variable and the independent variables?A. Cannot be knownB. MaybeC. NoD. Yes29. What will be the value of y if x = 0?A. -12.87 B. -0.08 C. 0.70 D. 0.99
Data on the price ($1000s) and the size (1000 ft2 sqaured) for 156 randomly selected houses that have been sold is summarized in the accompanying regression output and plots. Complete parts a and b a) Check the assumptions and conditions for inference. Select all that apply. A. The residuals look random. B. The residuals are nearly normal. C. The scatterplot looks straight enough. D. The residual plot and the scatterplot show consistent variability. E. None of the assumptions and conditions for inference are satisfied.
Data for 50 U.S. “states" was used to examine the relationship between violent crime rate (violent crimes per 100,000 persons per year) and the independent variables of urbanization (percentage of the population living in urban areas) and poverty rate. 50 observations were examined. The Excel sheet output for the analysis of this data is shown in the Figure (with some information intentionally left blank). SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.69 Standard Error 8.54 Observations 50 ANOVA df SS MS Significance F Regression 2060 54.9 0.000 Residual 47 18.77 Total 2942 Coefficients Standard Error t Stat P-value B0 B1 B2 31.9 148.2 -2.17 0.035 -4.6 1.654 2.83 0.007 39.3 13.52 2.91 0.006

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