escnet/w o/student/Assignment-Responses/last?dep=30597856#Q12Excel was used to determine the least squares regression equation. Part of the computer output is shown below.ANOVA?H₂ResidualTotalInterceptf2Regression 2 121.0625 60.5312 50.1910(x₂)(x₂)dff3SS9#10.854211 131.91673*Coefficients Standard Error t Stat120.0522-0.0181-1.5626MS1.2060f428.4829$(a) Use the output shown above and write an equation that can be used to predict the price of the stock. (Round your numerical values to four decimal place.)ý =F(b) Interpret the coefficients of the estimated regression equation that you found in part (a). (Give your answers in dollars. Round your answers to four decimal places.)As the number of shares of the stock sold goes up by 100 units, the stock price goes down by $goes up by 1 million, the stock price goes down by $0.0268 -0.68f50.3026 -5.16(c) At a 0.01 level of significance, determine which variables are significant and which are not.State the null and alternative hypotheses for the number of shares (in 100s) of company's stocks sold. (Enter != for # as needed.)Ho:4.21Find the value of the test statistic. (Round your answer to two decimal places.)%LC5Significance F0f60.0000P-value4-0.00230.516060.0006f74+when the volume of exchange on the NYSE is held constant. As the volume of exchange on the NYSEwhen the number of shares of the stock sold is held constant.&7f8IAAfg8DIIhpf10DDIPof12insertAprt sc23delete+backspacehomenumlockⒸend1:18 PM11/29/2022pg up6 escYou may need to use the appropriate technology to answer this question.The prices (in $) of Rawlston, Inc. stock (y) over a period of 12 days, the number of shares (in 100s) of company's stocks sold (x₁), and the volume of exchange (in millions) on the New York Stock Exchange (x₂) areshown below.?@Day213452 86.00 944 11.506789y1087.50 951 10.7584.00 939 11.50x₁83.00 929 12.0084.50 934 11.7584.00 936 12.7582.00 93380.00 93978.50 926x2Regression79.00 899 16.75Excel was used to determine the least squares regression equation. Part of the computer output is shown below.ANOVAResidual11 77.00 874 17.25Total12 77.50 869 17.25#13.50314.2515.25dfSS10.85422 121.0625 60.5312 50.1910131.9167f4$4MS1.2060f5%5Ff64-Significance F6f70.0000♫+&7f8IAA*fg811DIIhp(f10DDI11(12insertprt scdeletebackspacehomenumlockend1:18 PM11/29/2022pg up00pg dn

Solution: Given information: n= 12 observation k= 1 independent variables

Answered: ANOVA df Total SS Regression 2 121.0625…

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 B Miles Price (1000s) ($1000s) 22 29 36 47 63 77 73 87 92 101 110 28 59 68 68 91 42 65 110 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
You are studying the relationship between age and lung function measured as forced expiratory volume in 1 min. In a regression analysis is lung function the best option for Y? O Yes O No
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Refrigerator prices are affected by characteristics such as whether or not the refrigerator is on sale, whether or not it is listed as a Sub-Zero brand, the number of doors (one door or two doors), and the placement of the freezer compartment (top, side, or bottom). The table below shows the regression output from a regression model using the natural log of price as the dependent variable. The model was developed by the Bureau of Labor Statistics. Variable Coefficient Standard Error t Statistic Intercept 5.4000 0.13415 40.25 Sale price −0.0759 0.0283 −2.68 Sub-Zero brand 1.1471 0.1459 7.86 Total capacity (in cubic feet) 0.06929 0.00595 11.64 Two-door, freezer on bottom 0.05567 0.07292 0.76 Two-door, side freezer Base Two-door, freezer on top −0.3352 0.03537 −9.48 One door with freezer −0.6144 0.1362 −4.51 One door, no freezer −0.8573 0.1491 −5.75 Find the p-value for each coefficient, using 315 degrees of freedom. Using an α = .10, which predictor…
Suppose you wish to determine the degree to which annual earnings of professional golfers (Earnings) are related to driving distance (Yards Per Drive). The driving distance shows how far a golfer can hit the ball after it hits the ground. You were given the Excel output below. If the image below is not clear, dowload a copy here. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept Yards Per Drive 0.216543528 0.046891099 0.042101608 1155621.367 201 df 1 199 200 $$ 1.30747E+13 2.65757E+14 2.78831E+14 Coefficients Standard Error -7,773,135.558 30,737.523 2,867,254.773 9,823.548 4 MS 1.30747E+13 1.33546E+12 O a. a $30,737.523 increase in annual earnings. O b. a $9,823.548 increase in annual earnings. O c. a $2,867,254.773 increase in annual earnings. O d. a $7,773,135.558 decrease in annual earnings. t Stat -2.711002745 3.128963403 Figure 4.1 F 9.790411975 P-value 0.007294364 0.00201776…

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