Bridies and Score, How important are birdies ( a score of one under par on a given golf hole) in determining the final total score of a women golger? From the U. S women's open website, we obtained data on number of birdies during a tournament and final score for 63 women golfies. the data are presented on the Weiss Stats site.

a. Obtain the scatterplot for the data

b. Decide whether finding a regression line for the data is reasonable. if so, then also do parts (c)-(f)

c. Determine and interpret the regression equation for the data

d.Identify the potential outliers and influential observation

e. In case a potential outlier is present, remove it and discuss the effect.

f. In case potential influential observations is present,remove it and discuss the effect.

Short Answer

Expert verified

(a)

(b) Yes, it is reasonable

(c) The regression equation for the data is y^=304.5224-0.8209x

(d) There is no potential outliers and influential observation .

(e) Not applicable

(f) Not applicable

Step by step solution

01

Part(a) Step 1: Given Information

Given in the question that the U. S women's open website, we obtained data on number of birdies during a tournament and final score for 63 women golfers. the data are presented on the Weiss Stats site. we have to obtain the scatterplot for the data.

02

Part(a) Step 2: Explanation

03

Part(b) Step 1: Given Information

Given in the question that the U. S women's open website, we obtained data on number of birdies during a tournament and final score for 63 women golfers. the data are presented on the Weiss Stats site. we have to decide whether finding a regression line for the data is reasonable.

04

Part(b) Step 2: Explanation

If the scatterplot has no strong curvature, it is reasonable to find the regression line for the data.

Because the scatterplot has no strong curvature, it is reasonable to identify the regression line to the data. And the scatter plot show left to right downward tendency

05

Part(c) Step 1: Given Information

Given in the question that the U. S women's open website, we obtained data on number of birdies during a tournament and final score for 63 women golfers. the data are presented on the Weiss Stats site. we have to determine and interpret the regression equation for the data .

06

Part(c) Step 2: Explanation

Formula used to find the regression equation is

y^=b0+b1x

Where,

b1=-0.8209

b0=304.5224

Therefore,

y^=304.5224-0.8209x

07

Part(d) Step 1: Given Information 

Given in the question that the U. S women's open website, we obtained data on number of birdies during a tournament and final score for 63 women golfers. the data are presented on the Weiss Stats site. we have to identify the potential outliers and influential observation .

08

Part(d) Step 2: Explanation 

An outlier is a data point that is far off the regression line.

An influential observation is one where the removal of a point causes a significant change in the regression equation. That instance, removing a point causes a significant shift in the regression line's direction.

There are no potential outliers in the dataset because all of the points are closed to the regression line in the plotted graph. There is no considerable change in the direction of the regression line when a point is removed, hence there are no potentially influencing observations.

09

Part(e) Step 1: Given Information 

Given in the question that the U. S women's open website, we obtained data on number of birdies during a tournament and final score for 63 women golfers. the data are presented on the Weiss Stats site. we have to obtain in case a potential outlier is present, remove it and discuss the effect.

10

Part(e) Step 2: Explanation 

There are no outliers in part d so this is not applicable.

11

Part(f) Step 1: Given Information 

Given in the question that the U. S women's open website, we obtained data on number of birdies during a tournament and final score for 63 women golfers. the data are presented on the Weiss Stats site. we have to obtain in case potential influential observations is present,remove it and discuss the effect.

12

Part(f) Step 2: Explanation

There is no potential influential observation in part d. so this is not applicable.

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Most popular questions from this chapter

More Money, More Beer? The data for per capita income and per capita beer consumption for the 50states and Washington, D.C., from Exercise 4.77 are on the WeissStats site.

a. decide whether the use of the linear correlation coefficient as a descriptive measure for the data is appropriate. If so, then also do parts (b) and (c).

b. obtain the linear correlation coefficient.

c. interpret the value of Xin terms of the linear relationship between the mo variables in question.

As we noted, because of the regression identity, we can express the coefficient of determination in terms of the total sum of squares and the error sum of squares as r2=1-SSE/SST

a. Explain why this formula shows that the coefficient of determination can also be interpreted as the percentage reduction obtained in the total squared error by using the regression equation instead of the mean. Y¯. to predict the observed values of the response variable.

b.

x
6
6
6
2
2
5
4
5
1
4
y
290
280
295
425
384
315
355
325
425
325

What percentage reduction is obtained in the total squared error by using the regression equation instead of the mean of the observed prices to predict the observed prices?

a) Plot the data points and the first linear equation on one graph and the data points and the second linear equation on another.

(b) Construct tables forx,y,e,e2,y^

(c) Determine which line fits the data points better according to the least-square criterion.

12. In the context of regression analysis, what is an

a. outlier?

b. influential observation?

9. Based on the least-squares criterion, the line that best fits a set of data points is the one with the ________possible sum of squared errors.

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