5

Farmat Painter ClipkoztdPAnWEnSeeQUAN 3610 HW+Download the Baseball_Hitting_Data xlsx file from Canvas Run each of the following regressions using Fxcel Data Analys...

Question

Farmat Painter ClipkoztdPAnWEnSeeQUAN 3610 HW+Download the Baseball_Hitting_Data xlsx file from Canvas Run each of the following regressions using Fxcel Data Analysis Toolkit Use the Fxcel results to write down the eslimaled regression equalion For each regression equalion: inlerprel lhe slopes. inlerprel tbe P-value associaled iitb each slope. and inlerpret the Cvelficient of Delerminalion "R-squared" associated with the regression model Fxplain these results using language someone wh

Farmat Painter Clipkoztd PAnWEn See QUAN 3610 HW+ Download the Baseball_Hitting_Data xlsx file from Canvas Run each of the following regressions using Fxcel Data Analysis Toolkit Use the Fxcel results to write down the eslimaled regression equalion For each regression equalion: inlerprel lhe slopes. inlerprel tbe P-value associaled iitb each slope. and inlerpret the Cvelficient of Delerminalion "R-squared" associated with the regression model Fxplain these results using language someone who bas nuf laken slalislcs courye (D undersland Dependent variable: Batting Average Independenl varables: Runs Scored per Time Bal, Doubles per Tue Bal. Triples per Time al Bal Dependent variable: Batting Average Independent varables: Runs Scored per Time Bal, Doubles per Tue Bal. Triples per Time al Bal, Home Runs per Time Bal Dependent variable: Batting Average Independent variables: Runs Scored per Time al Bal, Doubles per Time Bal. Triples Pel Time al Bal; Home Runs per Time Bul; Slrike Oul per Times al Bat Was worth adding the Home Runs and Strike Out variahles to the regressions? Fxplain your reasoning 178 vorda 628 PM 110,2019 Type here search Nira F1gc



Answers

$$
\begin{array}{l}{\text { Use the data in NBASAL for this exercise. }} \\ {\text { (i) Estimate a linear regression model relating points per game to experience in the league and }} \\ {\text { position (guard, forward, or center). Include experience in quadratic form and use centers as the }} \\ {\text { base group. Report the results in the usual form. }}\end{array}
$$
$$
\begin{array}{l}{\text { (ii) Why do you not include all three position dummy variables in part (i)? }} \\ {\text { (iii) Holding experience fixed, does a guard score more than a center? How much more? Is the }} \\ {\text { difference statistically significant? }} \\ {\text { (iv) Now, add marital status to the equation. Holding position and experience fixed, are married }} \\ {\text { players more productive (based on points per game)? }}\end{array}
$$
$$
\begin{array}{l}{\text { (v) Add interactions of marital status with both experience variables. In this expanded model, is }} \\ {\text { there stronge evidence that marital status affects points per game? }} \\ {\text { (vi) Estimate the model from part (iv) but use assists per game as the dependent variable. Are there }} \\ {\text { any notable differences from part (iv)? Discuss. }}\end{array}
$$

In the first part of this problem, we will estimate a linear regression model where points depends on experience. The quadratic form of experience and their positions. This is the regression result table. You can see that we do not include all of the positions in their regression equation. There are three position cart forward and center. We drop center out of this equation because we don't want to fall into the dummy variable track. A dummy variable trap is happening when we have all the dummies. We have all the groups in the equation and we have perfect Monty Colin Arat e When that happened, well, most statistical Softwares will automatically drop one of the dummy out of the equation. It would not estimate one of the dummy, so you need not worry too much about including all the dummies in the equation. In this part, you will see you whether a guard scores more than a center. Now, you don't need to do any test. You just need to look at the estimation of the guard variable in the equation. It is so because the center is actually the based group. Okay, We have guard and forward as the attitude positions in the equation. The other group is the base group and the other group is the center position, so their coefficients of guard and forward would reflect the difference between these two positions and the based group, which is center. The coefficient of guard is 2.3, so it means a guard score more, then a center by its beta hat, which is 2.3. Okay, the P value is 0.21 So this beta has is significant and so the difference between the guard and their center is statistically significant in this part, we're going to add marital status, dummy into the regression equation. This is the result. Yeah, the coefficient of marital status dummy is 0.584 The T statistic is very small, and the P value is point for, given the P value of this variable greater than 0.1, this variable is not significant at the 10% level. So we are unable to conclude that marital status has any effect on the points scores by the players. In this part, we add marital status and its interaction term with experience and experience in quadratic form in the equation. We estimate the new equation with three variables related to marital status and this is the result. You can see that all three variables are not statistically significant. They're not significant at the 10% level. Yeah, we could also conduct an F test of joined significance. The null hypotheses under this F test is the beta of marital status and data of marital status interact with experience and the beta of marital status interact with the quality form of experienced equals zero. We will get the ABS statistic with the degrees of freedom of three and 261 equal 1.28 This is a very small number and the P value of this F test is 0.27 We are unable to reject the null hypotheses. We are going to replace the original dependent variable points with a new variable assists. We will estimate the same equation with explanatory variables experience experience in quadratic form, guard forward and marital status. We can tell the change in the estimation of marital status. The coefficient of marital status is now 0.3 to 2, and it's p value. It's not 0.149 So it means the beta means holding experience and position fixed. A marriage man has almost one third more assists per game. Okay, The P value also improves from the previous model where we have the dependent variable as points. However, it is still greater than 0.1. It means that at the 10% level, we are unable to conclude that married men are more productive.

The following estimated questions used the data in L A M L L MLB High, which contains information a major league baseball salaries. So the dependent variable s salary is the log of the salary and it's two explanatory variables. I s in the major leagues. I'm giving the equations. So the first question says, how many degrees or freedoms are in intra aggression and outcome there. CR is smaller in the second regression than in the first. So we're going to consider did some models first, which is which I'll be writing. Yes. And there's you create the other model is this'll Yeah, Klaus on this under here is so these are the two models on the formula to find the degree of freedom is showed as d f you think cost to end minus K plus one. So, yeah, the end is the sample size on the came first one is the number of estimated parameters. So the degree of freedom for the first regression would be D f because t o n minus K minus one and opened this and this is going to be called to 353 minus one, minus one. And is he called 35 phone. Now the degree of freedom for the second drink regression. So this is the first The second regression We d f equals toe end minus K minus one. This is the cause of 353 minus two minus one on this. Because the 3. 50 now in the second requestioning question the number of explanatory variables, um gets increased on. As a result, the SSR is increased on the S e l on s S s s are positively related. So s S R increases on S c r on S S r positivity related. Now the SCR decreases due to reducing beauty, reducing the value of the SSR. So this is the reason why this simple linear regression of smaller SCR values So the s e r decreases due to reduced value off the SSR. So that's what we can tell now moving on to the next question. The example Coalition coefficients between the years on r B. I S Y is about 0.487 Does this make sense? What is the various inflation factor for the slope coefficients in the multiple regression? Would you say there's lead to moderation or strong culinary ity between the years on the r B I s Y are so for this to crush coalition coefficient, the coalition represents the information. So for values between 1.0 on 0.5, they have strong linear relationship for bodies between 0.3 um 0.5. They have moderate post it Steve Linear relationship Now for values between their points, one on 0.3 have weak, positive linear relationship. Now for values that was their points would have no or very weak linear relationship. So the correlation between the years correlation between yes on and that is 0.487 on it's considered the correlation is moderately. Since it's this, it's moderately positive is going to be on this. So is moderately positive in nature because it's close to 0.5. So therefore it makes sense, right, And now the various inflation factor can be calculated. US. V. I f is the cost to one divided by one minus R squared. Yes, on R squared yes is equal to 0.5 597 So put values of our square years in a formula and you get one divided by one minus 0.597 on this, because toe one divided by 0.403 So the f is two point for 814 So therefore, this is the V F on. This represents the value below the value. One is that values. Remember that valley one. What you want is values. The are not coral. It said valleys between one on four. Our values that moderately correlated values that greater than four. Our values the I li correlated so we can tell that 2.4814 represents value. Mr um Moderately correlated. So there's a moderates, Corrine ality between the years and the RBS I as valued lazier. So that is in moderate called narrative. Okay. Between? Yes, um, yeah, as via ev. Nice between, what? On fourth? Yeah, Now moving on. How come the standard error for the coefficient on years in the multiple regression is lower than its counterparts in the simple regression? So, in the second regression equation, do you know about explanatory variables get increased and as a result, S S R is increased on S e. R. On S S R is positively related. Now the SCR decreases due to the value off reducing value off this. So s E r. Decree this, dude. So the reducing value off S S r on This is the reason why simple in the immigration have smaller S e r values.

Part one. This is an estimation result for the linear trend model. Using the first 119 Observations. And excluding the last 12 months, We have our square of .28 and the standard error of the regression Is 288.33 are too. If we estimate an A. R. One model excluding the last 12 months, this is what we get. Oh, our number of observations or degree of freedom. Now Number of observations we use in the model is 118 one less than the previous equation. The R Square is now lower .17 and the standard error of the regression is now over 300. So based on the R. Square and they're centered heroines of the re question, we can conclude that the linear trend model is a better fit to the data. A good model would have a high are square and a low send it errol of regression. When we compare the two models by measures of a rod's. We have R. M. S. E. Of the linear trend equation of 300 15 point right. And so that the route mean square of peril and for their mean absolute error O. M. E. We have 200,000 1.9 For the linear trend model. For the a. r. one model, The two values are 388.6 and 246.1 respectively. The A. R. one has higher measures of arrows compared to the linear trend. So again we conclude that the linear trend is a better fit to the data. In part four, we test this joint significance of their monthly dummies. The f statistic with 11 and 107 degrees of freedom is 1.15 with a p value of 0.3 28 Mhm. So we are unable to reject the null hypothesis, meaning we don't need to account for the seasonality in for casting C H. N. I am p.

Part one. The dickey Fuller statistic is -3.31 which is To the left of the 2.5 critical value of -3 12 So using this test we can reject a unit root. Uh huh. The 2.5 level or two. When we add to lag change to the regression in part one, the test statistic become yeah -1.5. And the estimated route about .915. Previously the estimated route is 0.81 So in part two we find Lato evidence against a unit root. Part three, We add a time trend to the model. In part two, the ADF statistic Is -3.67. The estimated route is 0.5 seven. The 2.5 critical value Is -3.66. So we are back To the same conclusion as in part one. We reject. Are you need direct part four? We should better characteristics the data with An integrated zero model, Part 54 P r c f a t. The augmented dickey fuller test without trend Is -4.74 With an estimated route of .62 with a tam trinh. The ADF test is minus five point 29 and an estimated route is .54. So here the evidence is strongly in favor of A zero Integrated process, regardless of including a trend or not.


Similar Solved Questions

5 answers
Wh 1 1 Problem: [ the volume [ rotating region enclosedand y xwith y 2 0
Wh 1 1 Problem: [ the volume [ rotating region enclosed and y xwith y 2 0...
5 answers
11 . (16 points) Let € be the circular region given parametrically by (a cos t,a sin t) ,0 < t < 2r with a counterclockwise CIRCULATION. Evaluate the lineintegralydx + xdyDirectly (i.e. fmt y)dx N(x,y)dy)ON dxdM dA)b Using Green's Theorem (i.e
11 . (16 points) Let € be the circular region given parametrically by (a cos t,a sin t) ,0 < t < 2r with a counterclockwise CIRCULATION. Evaluate the line integral ydx + xdy Directly (i.e. fmt y)dx N(x,y)dy) ON dx dM dA) b Using Green's Theorem (i.e...
5 answers
X1,X2, 'Xn are jid random variables having pdf f(xle) 40x3e-8x+ I(0,_ c (*)where 0 €o (0, 6). Obtain an exact 99% confidence interval for 0 which depends on the xi only through the value of the complete sufficient statistic Ei-1 X4 and evaluate it for the case of n 10 and Ex' 23,6, rounding each confidence bound to the nearest hundredth
X1,X2, 'Xn are jid random variables having pdf f(xle) 40x3e-8x+ I(0,_ c (*) where 0 €o (0, 6). Obtain an exact 99% confidence interval for 0 which depends on the xi only through the value of the complete sufficient statistic Ei-1 X4 and evaluate it for the case of n 10 and Ex' 2...
5 answers
2 Two Polaroids are placed into the unpolarized beam of' a light source. The angle between the axes of polarization of the two Polaroids is 30* . If the intensity of the incident beam is 1o, what is the intensity of the trans- mitted light?
2 Two Polaroids are placed into the unpolarized beam of' a light source. The angle between the axes of polarization of the two Polaroids is 30* . If the intensity of the incident beam is 1o, what is the intensity of the trans- mitted light?...
5 answers
Suppose WC label all the vertices of a rooted tree T with numbers_ These labels obey the property that every vertex has a label larger than the labels of its children (the vertices that it'$ connected to below it). Prove by structural induction that the root has the largest label in the tree
Suppose WC label all the vertices of a rooted tree T with numbers_ These labels obey the property that every vertex has a label larger than the labels of its children (the vertices that it'$ connected to below it). Prove by structural induction that the root has the largest label in the tree...
5 answers
7 . Draw a mechanism for the following thiamin-dependent reaction. (6P)COOCOOCOzOH
7 . Draw a mechanism for the following thiamin-dependent reaction. (6P) COO COO COz OH...
5 answers
Eclr Integral.Iuleeali? (+21 Ful te Inmudarythie circulau S0 < <2/3 V<r< R}letting RHHMtFor JII pithe Wupt "> gcuieralizs thts uutt hdl UHACherk Jeult 4SN Iw WAkIWg 4Ig" o vatr Iublen lat-AT for which You EleMe MetCe thcs probkmKt
Eclr Integral. Iuleeali? (+21 Ful te Inmudary thie circulau S 0 < <2/3 V<r< R} letting R HHMt For JII pithe Wupt "> gcuieralizs thts uutt hdl UHA Cherk Jeult 4SN Iw WAkIWg 4Ig" o vatr Iublen lat-AT for which You EleMe Met Ce thcs probkm Kt...
5 answers
[-/4.54 Points]DETAILSSCALCET8 10.2.011,Find dyldx and dkyldx? . t2 + 8, =t2 + 9tFor which values of t is the curve concave upward? (Enter your answer using interval notation_Need Help?Rezd ItMaabn
[-/4.54 Points] DETAILS SCALCET8 10.2.011, Find dyldx and dkyldx? . t2 + 8, =t2 + 9t For which values of t is the curve concave upward? (Enter your answer using interval notation_ Need Help? Rezd It Maabn...
4 answers
Draw the final product with stereochemistry and lone pairs. The leaving group has been pre-drawn for your convenienceSelectDrawRingsMoreErase3 QWhat is the absolute configuration of the chloroethane final product?
Draw the final product with stereochemistry and lone pairs. The leaving group has been pre-drawn for your convenience Select Draw Rings More Erase 3 Q What is the absolute configuration of the chloroethane final product?...
5 answers
Find the center, the vertices, the foci, the asymptotes, and the length of the transverse axis of the hyperbola with equation $x y=1 .$ HTNT: Define new $X Y$ -coordinates by selling $x=X+Y$ and $y=X-Y.$
Find the center, the vertices, the foci, the asymptotes, and the length of the transverse axis of the hyperbola with equation $x y=1 .$ HTNT: Define new $X Y$ -coordinates by selling $x=X+Y$ and $y=X-Y.$...
1 answers
In Exercises $51-66,$ find a. $(f \circ g)(x)$ b. $(g \circ f)(x)$ c. $(f \circ g)(2)$ d. $(g \circ f)(2)$ $$ f(x)=\frac{1}{x}, g(x)=\frac{1}{x} $$
In Exercises $51-66,$ find a. $(f \circ g)(x)$ b. $(g \circ f)(x)$ c. $(f \circ g)(2)$ d. $(g \circ f)(2)$ $$ f(x)=\frac{1}{x}, g(x)=\frac{1}{x} $$...
5 answers
A wave traveling along the x axis is described mathematically bythe equation y = 0.17sin(8.7Ï€t + 0.60Ï€x), where y is thedisplacement (in meters), t is in seconds, and x is in meters. Whatis the speed of the wave?
A wave traveling along the x axis is described mathematically by the equation y = 0.17sin(8.7Ï€t + 0.60Ï€x), where y is the displacement (in meters), t is in seconds, and x is in meters. What is the speed of the wave?...
1 answers
Number of voters Ist choice Znd choice 3rd choice141310C | B | A A | A | BB / CFind the winner of this election under the Borda Count method.Winner
Number of voters Ist choice Znd choice 3rd choice 14 13 10 C | B | A A | A | B B / C Find the winner of this election under the Borda Count method. Winner...

-- 0.019610--