9. Regression of y= Bo + B1X11 + B2X12 + B3 X13 + BaX14 + û¡ yieldsthe following results in tabular form. The tabulated t- statistics is 2.4 , 1.96and 1.64 for onefive and ten percent significance levels respectively.State the null and alternative hypotheses for each & Identify those variablesaffecting the dependent variable.Independent variablesCoefficientsStd. Err.Xi11731.784255.4491Xi2667.8642250.4062Xi3-38.44927200.0217Xi4-48.14751423.5669Bo3559.713243.1407

There are 4 independent samples and 1 dependent variable. The partial regression analysis output is…

Answered: 9. Regression of y=Bo + B1xi1 + the…

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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Given are five observations for two variables, and y. The estimated regression equation for these data is = 75.74-2.92x. a. Compute SSE, SST, and SSR. Yi The least squares line provided an - Select your answer decimal). fit; 4 SSE (to 2 decimals) SST (to 2 decimals) SSR (to 2 decimals) b. Compute the coefficient of determination ². Comment on the goodness of fit. (to 3 decimals) 00 15 18 20 57 57 46 17 12 Check My Work (2 remaining) % of the variability in y has been explained by the estimated regression equation (to 1 c. Compute the sample correlation coefficient. Enter negative value as negative number. (to 3 decimals)
Confidence intervals for a mean: Normal population (p=80, o=10) Type=z (... Sample size=5 CI Level Containing p Total Proportion 0.9 2163 2400 0.9012 50 60 70 90 100 T10 80 Intervals 2301 to 2400 The following is a graph of Applets simulated confidence intervals a) The value of the hypothesized population mean Ho = (Enter an integer) b) The total number of confidence intervals simmulated is, and the percent of these total intervals that contain the population mean c) The percent of last 100 intervals that contain the population mean is equal to %(entr an interger) d) In the long run, the percent of all intervals that will contain the population mean is approximate equal to %(entr an interger) equal to %(keep two digits after decimal point)
Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.883 and the least squares regression line is y = 0.134x + 13.693. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 27.75 25.25 26 25.25 27.25 26.75 26 27.25 27 27.25 26.75 17.1 17.3 17.0 17.4 17.2 17.2 17.3 17.3 17.4 17.3 ..... (a) Compute the coefficient of determination, R?. R? % (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. Approximately % of the variation in is explained by the least-squares gression model. (Round to one decimal place as needed.)
For the population of college students, the number of hours spent studying per week is normally distributed with a = 4.40 and = 2.32 hours. We surveyed a random sample of students majoring in psychology about the number of hours they spent studying this past week. The data is as follows: 6, 8, 9, 4, 3, 11, 4, 6, 5, 7 What is the dependent variable? What is the level of measurement of the dependent variable? 3. Is there a significant increase in the number of hours spent studying for our sample compared to the population of college students? Perform a complete hypothesis test (z-test) using alpha = .01 level. SHOW ALL WORK
Need help writing a null hypothesis for the bivariate relationship shown in the SPSS output.
o pis pe Suppose a doctor measures the height, x, and head circumference, y. of 11 children and obtains the data below. The correlation coefficient is 0.899 and the least squares regression line is y = 0.185x+ 12.276. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 17.1 17.2 16.9 17.4 17.1 17.1 17.3 17.3 17.3 17.4 27.75 25.75 26.75 25.75 28 26.5 25.75 26.75 27 27.25 27.25 (a) Compute the coefficient of determination, R?. R2 = % (Round to one decimal place as needed) (b) Interpret the coefficient of determination k Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. Enter your answer in each of the answer boxes. Save for Later DUE RTTT:DY PIVT Score: o:5SYO Tor Tv attempts 3:35 PA- a 2/22/202 Type here to search insert prt sc 4+ backsp %23 6. 8.
In a multiple regression, which of the following tests can be used to determine if the relationship between the dependent variable and the set of independent variables is significant? The Coefficient Of Determination R-Squared for each coefficient of the X variables & an F- Statistic Test for the overall regression F-Statistic tests for each coefficient & a t-test for the overall regression The Coefficient Of Determination R-Squared and/or an F-Statistic Test for the overall regression & t-tests for each coefficient of the X variables t-tests for each coefficient and for the overall regression
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e) Perform the F Test making sure to state the null and alternative hypothesis.
Consider the following computer output from a multiple regression analysis relating the cost of car insurance to the variables: number of car accidents, driver's credit score, and safety rating of the car. Intercept Car Accidents (In last 3 years) Credit Score Safety Rating Coefficients 1186 213.48 Coefficients - 130.46 294.11 Standard Error Does the sign of the coefficient for the variable safety rating make sense? 123.87 21.89 14.26 356.37 t Stat P-value 9.575 0.0000 9.752 0.0000 -9.149 0.0000 0.825 0.4128
Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.858 and the least squares regression line is y = 0.228x +11.187. Complete parts (a) and (b) below. Height, x 27.5 25.75 26.5 25.5 27.25 26.25 25.75 27.25 27 27.25 27 Head Circumference, y 17.4 17.2 17.2 16.9 17.6 17.1 17.1 17.4 17.4 17.3 17.3 (a) Compute the coefficient of determination, R². R² =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment on the adequacy of the linear model. Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. According to the residual plot, the linear model appears to be
Here are the scatter plots for two sets of bivariate data with the same response variable. The first compares the variables x & y. The second compares the variables w & y 098 Which explanatory variable has a stronger relationship with the response variable y? O The first variable (x) has a stronger relationship with the response variable y. O The second variable (w) has a stronger relationship with the response variable y.

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