Identify the critical value and rejection region of the following problems. Sketch the curve for each problem. 2. A school district is trying to determine if its standardized test scores are higher than thenational average which is 92 points. From a sample of 45 students, the average scorewas 89 points with a standard deviation of 12 points. Test the hypothesis at a = 0.05

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Answered: 2. A school district is trying to…

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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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 table below. Calculate the least square estimates of slope and intercept. Sale Price/1000 Taxes/1000 ... 25.9 4.9176 29.5 5.0208 27.9 4.5429 4.5573 5.0597 3.8910 25.9 29.9 29.9 30.9 28.9 35.9 5.0980 5.6039 5.8282 31.5 5.3003 31.0 6.2712 30.9 5.9592 30.0 5.0500 36.9 8.2464 41.9 6.6909 40.5 7.7841 43.9 9.0384 37.5 5.9894 37.9 7.5422 44.5 8.7951 37.9 6.0831 34.9 8.3607 8.1400 26.9 45.8 9.1416 Input answers up to 3 decimal places. Slope 3.324 Intercept 13.320 Blank 1 3.324 Blank 2 13.320
Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 130 to 190 cm and weights of 41 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x = 167.53 cm, y 81.32 kg, r 0.259, P-value 0.009, and y = 106+ 1.09x. Find the best predicted value of y (weight) given an adult male who is 181 cm tall. Use a 0.10 significance lev. The best predicted value of y for an adult male who is 181 cm tall is kg. (Round to two decimal places as needed.)
1. Consider the following regression model: Fram Risk Score; = Bo + B1 × Health Insurance; + u¿ The Framingham Risk Score predicts 10-year risk of cardiovascular disease based on age, cholesterol levels, blood pressure, blood sugar, use of medication for high blood pressure, and smoking. A higher score means worse overall cardiovascular health. A researcher who collects data and regresses the Fram Risk Score against Health Insurance (= 1 if have insurance) finds that B, 2. Consider the following regression model: Class Average; = Bo + B1 x Office Hours; + u; Class Average is the students' average grade in the class at the end of the term and Office Hours is the number of office hours held by the instructor over the entire term. A researcher who collects data and regresses Class Average against Office Hours finds that, surprisingly, B V A V A
Thirty data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bx. The computer output from the regression analysis is DEPENDENT VARIABLE: R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 30 0.5300 13.79 0.0009 VARIABLE PARAMETER STANDARD T-RATIO P-VALUE ESTIMATE ERROR INTERCEPT 93.54 46.210 2.02 0.0526 |-3.25 0.875 |-3.71 0.0009 At the 1% level of significance, the critical t-value for the test is (Write the numbers as they are, do not round them)
2. For the Powder Cocaine Stigmatization regression equation in Table 3, a. Interpret the parameter estimate for Age 20-22 b. Interpret the parameter estimate for Hispanic/Latino
The I-85 Carpet Outlet wants to develop a means to forecastits carpet sales. The store manager believes that the store’s sales are directly related to the number of new housing starts in town. The manager has gathered data from county records of monthly house construction permits and from store records on monthly sales. These data are as follows: a. Develop a linear regression model for this data and forecast carpet sales if 25 construction permits for new homes are filed. b. Determine the strength of the causal relationship be- tween monthly sales and new home construction using correlation. Monthly Carpet Sales Monthly Construction(1000s yd) Permits5 1712 306 125 14
Show necessary calculation/justification for each answer. a) In regression analysis, the residuals represent the:a. difference between the actual y values and their predicted values.b. difference between the actual x values and their predicted values.c. square root of the slope of the regression line.d. change in y per unit change in x. b) The least squares method for determining the best fit minimizes:a. total variation in the dependent variableb. sum of squares for errorc. sum of squares for regressiond. All of these choices are true. c) The regression line has been fitted to the data points (4, 8), (2, 5), and (1, 2).The sum of the squared residuals will be:a. 7b. 15c. 8d. 22

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2. A school district is trying to determine if its standardized test scores are higher than the national average which is 92 points. From a sample of 45 students, the average score was 89 points with a standard deviation of 12 points. Test the hypothesis at a = 0.05