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Research Process Paper

Research Process Paper
Research is defined as the organized, systematic, critical investigation into a specific problem. Team A has been tasked with three problems to solve for all managers of the National and American Baseball Leagues: 1) Is the Earned Run Average (ERA) a significant predictor of the teams' overall wins? 2) Are Attendance, Batting, ERA, Home Runs (HR) and Error the significant predictors of the Wins? 3) Does the mean team salary affect wins? (Lind, Marchal, &Wathen, 2008) provides the basic primary research in their Major League Baseball Data Set as seen below.
X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15

Team League Built Size Surface Salary Salary -mil Wins Attendance Batting ERA HR Error SB Year Average
Boston 1 1912 33871 0 123505125.0 123.5 95.0 2,847,798 0.281 4.74 199 109 45 1989 512,930
New York Yankees 1 1923 57746 0 208306817.0 208.3 95.0 4,090,440 0.276 4.52 229 95 84 1990 578,930
Oakland 1 1966 43662 0 55425762.0 55.4 88.0 2,108,818 0.262 3.69 155 88 31 1991 891,188
Baltimore 1 1992 48262 0 73914333.0 73.9 74.0 2,623,904 0.269 4.56 189 107 83 1992 1,084,408
Los Angles Angels 1 1966 45050 0 97725322.0 97.7 95.0 3,404,636 0.270 3.68 147 87 161 1993 1,120,254
Cleveland 1 1994 43368 0 41502500.0 41.5 93.0 2,014,220 0.271 3.61 207 106 62 1994 1,188,679
Chicago White Sox 1 1991 44321 0 75178000.0 75.2 99.0 2,342,804 0.262 3.61 200 94 137 1995 1,071,029
Toronto 1 1989 50516 1 45719500.0 45.7 80.0 2,014,995 0.265 4.06 136 95 72 1996 1,176,967
Minnesota 1 1982 48678 1 56186000.0 56.2 83.0 2,034,243 0.259 3.71 134 102 102 1997 1,383,578
Tampa Bay 1 1990 44027 1 29679067.0 29.7 67.0 1,141,915 0.274 5.39 157 124 151 1998 1,441,406
Texas 1 1994 52000 0 55849000.0 55.8 79.0 2,525,259 0.267 4.96 260 108 67 1999 1,720,050
Detroit 1 2000 40000 0 69092000.0 69.1 71.0 2,024,505 0.272 4.51 168 110 66 2000 1,988,034
Seattle 1 1999 45611 0 87754334.0 87.8 69.0 2,724,859 0.256 4.49 130 86 102 2001 2,264,403
Kansas City 1 1973 40529 0 36881000.0 36.9 56.0 1,371,181 0.263 5.49 126 125 53 2002 2,383,235
Atlanta 0 1993 50062 0 86457302.0 86.5 90.0 2,520,904 0.265 3.98 184 86 92 2003 2,555,476
Arizona 0 1998 49075 0 62329166.0 62.3 77.0 2,059,327 0.256 4.84 191 94 67 2004 2,486,609
Houston 0 2000 42000 0 76799000.0 76.8 89.0 2,805,060 0.256 3.51 161 89 115 2005 2,632,655
Cincinnati 0 2003 42,059 0 61892583.0 61.9 73.0 1,923,254 0.261 5.15 222 104 72
New York Mets 0 1964 55775 0 101305821.0 101.3 83.0 2,827,549 0.258 3.76 175 106 153
Pittsburgh 0 2001 38127 0 38133000.0 38.1 67.0 1,817,245 0.259 4.42 139 117 73
Los Angeles Dodgers 0 1962 56000 0 83039000.0 83.0 71.0 3,603,680 0.253 4.38 149 106 58
San Diego 0 2004 42,445 0 63290833.0 63.3 82.0 2,869,787 0.257 4.13 130 109 99
Washington 0 1961 56000 0 48581500.0 48.6 81.0 2,730,352 0.252 3.87 117 92 45
San Francisco 0 2000 40800 0 90199500.0 90.2 75.0 3,181,020 0.261 4.33 128 90 71
St Louis 0 1966 49625 0 92106833.0 92.1 100.0 3,542,271 0.270 3.49 170 100 83
Florida 0 1987 42531 0 60408834.0 60.4 83.0 1,852,608 0.272 4.16 128 103 96
Philadelphia 0 2004 43500 0 95522000.0 95.5 88.0 2,665,304 0.270 4.21 167 90 116
Milwaukee 0 2001 42400 0 39934833.0 39.9 81.0 2,211,323 0.259 3.97 175 119 79
Chicago Cubs 0 1914 38957 0 87032933.0 87.0 79.0 3,100,092 0.270 4.19 194 101 65
Colorado 0 1995 50381 0 48155000.0 48.2 67.0 1,914,385 0.267 5.13 150 118 65

In the below scatter plot there is a significantly negative (inverse) correlation between Earned Run average and Wins.

(Lind, Marchal, &Wathen, 2008)
The statisticians of Team A define and address each problem in an effort to present information to the league managers regarding conceptual issues and areas for improvement.
Problem #1
Is the Earned Run Average (ERA) a significant predictor of the teams' overall wins? For this research question the testable hypotheses are:
Null hypothesis: The ERA is not a significant predictor of the Wins.
Alternative hypothesis: The ERA is a significant predictor of the Wins.
Problem #2
Are Attendance, Batting, Home Runs, and Error the significant predictors of the Wins? For this question the testable hypotheses are:
H01: The fitted regression equation is not significant.
Ha1: The fitted regression equation is significant.
H02: The regression coefficient of independent variable is not significant.
Ha2: The regression coefficient of independent variable is significant.
In this question the dependent variables are the wins and the independent variables are attendance, ERA's, batting, home runs, and errors.
Problem #3
Does the mean salary of each team affect the amount of wins? In this question the
Null hypothesis: The mean team salary does affect the amount of wins.
Alternative hypothesis: The mean team salary of team does not affect wins
Three possible outcomes of this analysis might be: 1) the ERA is a significant predictor of wins, 2) Attendance, Batting, Home Runs, and Error are the significant predictors of the wins or 3) The team mean salaries affect the overall amount of wins.
Measurement Scales
There are four scales of measurement: nominal, ordinal, interval, and ratio. The ratio scale is the highest form of measurement. It is similar to the interval scale because it represents quantity and has equal units. There is; however, a value to "0". A negative number is not possible. The measurement scale used in this research is the ratio scale. Regarding Problem #1, in the scatter plot, we are comparing the team's earned run average with the number of games the team wins. The differences between wins is quantifiable and can be expressed in a ratio. At the beginning of baseball season, both the earned run average and the number of wins start at a "0" value and never goes below "0."
In Problem # 2, we are comparing attendance, batting, earned run average, home runs, and errors which all start with "0" values and never go below "0." In Problem #3, we are comparing the mean salaries of team against wins. Specific figures are used. The mean salary of each team is the salaries added together and divided by the number of team members.
Variables and level of Measurement
Understanding that all of the data sets for this assignment are related to baseball stats and are thus numerical, the level of measurement used by Team A on this assignment was the ordinal scale. The ordinal scale will allow Team A to capture the mean of the items related to the sport. Team wins, fan attendance, batting and earned run averages, as well as the total home runs and errors made by the team allow us to use the statistical median of each variable to rank the correlation of the ordinal data. In addition, we used the frequency tables and cross tabulations within the ordinal scale to calculate the data. As result, Team A will be able to adequately validate its research and prove that increased batting averages, decreased earned run averages and errors by a particular team, usually leads to an increased winning percentage by a particular team

• Define operational definitions for each variable.
.

Remaining Research Steps

Our main research question is: Is the Earned Run Average (ERA) a significant predictor of the teams' overall wins. In our subsequent research we will also question whether the attendance, batting, home runs, and errors affect the overall wins. We will also question whether the mean team salaries of the American and National Leagues are significant.
The next step in the preliminary research gathering is the literature review where the researchers will conclude the relevant variables and proceed with a good basic framework for further investigation. Our literature reviews will ensure a clearer view of variables tested to write the hypotheses knowing what is already known and what still needs investigation. The team will then summarize the peer-reviewed articles describing how they relate to our research.
Next the team will perform an analysis based on data collection. They will display data as a histogram, frequency distribution, and other graphical exhibits. In addition, the central tendencies and dispersions will be shown as well as the confidence interval regarding the research questions. In conclusion, Team A will come to a conclusion and make recommendations to the team managers regarding the research findings.

References
Lind, Marchal, and Wathen. (2008). Statistical Techniques in Business & Economics, 13th edition. New York, NY: McGraw-Hill

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Lazear. E (1986) "Salaries and Piece Rates", The Journal of Business
Vol. 59, No. 3 (Jul.), pp. 405-431

This article is related to the research paper because the research paper focuses on "are Attendance, batting, home run and error the significant predictors of the wins? In case of this paper the focus is if piece rate is closely related to the output of the worker? The question your paper is exploring if the mean salary of the team affects the amount of wins? The question that this paper explores is how the difference in the mode of payment can significantly affect out put of employees. In other words this article says that if instead of a fixed salary piece rate was paid, it ...

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