In a simple linear regression problem, the following statistics are calculated from asample of 10 observations:= 50,(x-7)(y-y)= 2250, s,= 10,xΣy= 75. The least squares estimates of the slope and y-intercept are respectively:1.5 and 0.52.5 and 1.5c. 1.5 and 2.5d. 2.5 and -5.0If a simple linear regression model has no y-intercept, then:all values of x are zerob.all values of y are zeroc. when y = 0 so does xwhen x = 0 so does yd.a.b.a.

We have given a simple linear regression problem. Number of observations, n = 10 ∑x-x¯y-y¯ =…

Answered: In a simple linear regression problem,…

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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Using 23 observations on each variable, a computer program generated the following multiple regression model. y = 65.5 +9.56x1+3.27x2-4.23x3– 9.23x4 If the standard errors of the coefficients of the independent variables are, respectively, 3.44, 2.30, 2.76, and 4.99, can you conclude that the independent variable x, is needed in the regression model? Let B1, B2, Ba denote the coefficients of the 4 variables in this model, and use a two-sided hypothesis test and significance level of 0.10 to determine your 4 .../ answer. (a) State the null hypothesis H, and the alternative hypothesis H,. H, : 0 H, : 0 (b) Determine the type of test statistic to use. Degrees of freedom: D=0 OSO (c) Find the value of the test statistic. (Round to two or more decimal places.) O#0 OO (d) Find the two critical values at the 0.10 level of significance. (Round to two or more decimal places.) | and || (e) Can you conclude that the independent variable is needed in the regression model? Yes No 미
Use multiple linear regression fit of the form y = a + bx₁ + cx₂ for the following data: 1.5 3 3 -1 X₁0 01 2 1 X₂ 0 1 0 1 2 1 2 3 -1 -2 -1.5 -12 -15 17 y 1644
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.5 8.2 6.9 3.3 2.8 2.2 2.6 0.6 yy 13.7 10.9 10.2 7 6.1 5.8 6.3 4.2 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.87x+3.9.y=0.87x+3.9. Use this equation to answer the following;A) How many murders per 100,000 residents can be expected in a state with 2.5 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 5.2 thousand automatic weapons?Answer = Round to 3 decimal places. Submit QuestionQuestion 17
Compute the least-squares regression equation for the given data set. Use a Ti-84 caloulator. Round the slope and at least four decimal places. 4 6 12 -9 -3 5 -11 3. 31 36 3 -2 -14 Send data to Excel Regression line equation: y =I
Use the following information to answer questions 6 and 7. In a study, nine tires of a particular brand were driven on a track under identical conditions. Each tire was driven a particular controlled distance (measured in thousands of miles) and the tread depth was measured after the drive. Tread depth is measured in "mils." Here, 1 mil is 0.001 inch. The least-squares regression line was computed and added to a scatterplot of these data. On the plot, one data point is marked with an "X." The equation of the least-squares regression line is: Tread depth = 360.64 - 11.39 Miles The data value marked with "X" in the provided scatterplot has Tread Depth (Mils) 60 80 150 0 5 O a negative value for the residual. O a positive value for the residual. O a zero value for the residual. O a zero value for the correlation. 10 15 Miles (x 1000) 20 25 30
Consider the following data values for variables x and y: Ť 8 10 5 2 3 1 X 5 4 3 6 9 8 10 The regression coefficients were calculated as bo = 13.223 and b₁ = -1.257. Select the correct statement. Select one: O a. If x = 2, the estimated value of y from the regression line is -25.189. b. The least--squares regression line is y = 13.223-1.257x. c. An x-value of 11 resulted in an estimated y value of -1.861 d. The least--squares regression line is y = 1.257-13.223x. e. The relationship between x and y appears to be linear and positive.
7. Find slop of a linear regression model for the following data: x = [1, 2, 3, 4, 5, 6, 7] z = [ 1.40, 3.78, 4.41, 4.60, 8.40, 8.64, 12.81]. -1.7 -0.5 0.5 O 1.7 CS Scanned with CamScannel
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)
in simple linear regression, given the following table : n = 25 E(y,-7) = 1407 %3D SSR = 472 Calculate the standard error of the estimate (s): Select one: Oa. 7.82 Ob. 6.38 Oc. 58.62 d. 34.63 Next
4. Consider a multiple linear regression model with two independent variables with 12 values in each variable. The coefficient of determination is obtained as 0.58. Evaluate the adjusted coefficient of detemination. for f nding Tote1 Cam ltinle lincor
Given below are five observations collected in a regression study on two variables x (independent variable) and y (dependent variable). X Y 10 7 20 5 30 4 40 2 50 1 a. Develop the least squares estimated regression equation. b. At the 5% level of significance, perform a t test and determine whether or not the slope is significantly different from zero. d. Compute the coefficient of determination. e. Compute the coefficient of correlation.

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