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Data Collection Major League Baseball

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Data Collection Paper (MLB) Laura L. Mason, Becky Matlock, and Nichole Noble RES/341 June 8, 2011 David Morrisson Data Collection Paper (MLB) Data collection is an important part of research and it requires that the right information be collected. Because of many types of data research it is imperative to make sure the data collected is present in the final analysis. This data can be shown in different formats such a graphical or tabular. Team A has chosen the Major League Baseball (MLB) data set and feels the population and the type of data collected will provide good resources for surveys to make informed decisions. Team A will review the types of ways data can be shown as well as some of the ethical issues that researchers may run into. Our research involves looking at the 30 MLB teams in how the statistics vary. The data set is a accumulation of information that includes what league they are in, the year of erection of each stadium, capacity of each stadium, salary of the team, wins for the season, batting average, attendance, earned run average (ERA), stolen bases (SB), and home runs (HR). The sample for this research topic is very sufficient. It includes all the teams in the league and portrays the same information for all of the teams. The population (teams) and the categories listed in the data set will provide Team A the information to complete our research into whether or not a higher salary will make a team better. In reviewing the article titled “Work Incentives and Salary Distributions in Major League Baseball,” the author, Brandon Avrutin, discusses the relationship between the payroll and the performance of the team. According the Avrutin, “the more equally the payroll distribution is among team members, the better the on-field performance of the team” (Avrutin & Sommers, 2009) (pg1). The article further goes on to discuss the top and bottom teams of the 2005 season. “In 2005, the top two Gini coefficients belonged to the New York Yankees and the Boston Red Sox (both with 0.586 win percentages); the bottom two Gini coefficients belonged to the Colorado Rockies and the Kansas City Royals (with win percentages of 0.414 and 0.346, respectively). In general, one can conclude that for the 2001–2005 period more equal salary distributions in MLB do not lead to better on-field performance,” (Avrutin & Sommers, 2009) (pg2). Sampling according to WordIQ.com is the part of statistical practice regarding the selection of individual comments intended to surrender some facts about a set of entities concerning, which interprets statistical data. For example, results from the mathematical study of probability and the theory of statistics are in use to guide practice. The sampling process has five stages: 1. Meaning of population of concern 2. Measurement of a sampling outline, possible to measure 3. Measurement of sampling method for choosing events from the outline 4. Data and sampling collecting 5. Analysis of sampling procedure When sampling validity and reliability possible sources of bias or error may occur, some possible sources of bias could come from almost any factor affecting the baseball managers, organization, or even from a hired third-party collecting data for the sampling. The random sampling method for research purposes in the “Productive Efficiency and Salary Distribution case of US Major League Baseball” journal article (Jewell & Molina, 2004). Summarizing the article the recent academic studies suggest a baseball organization’s income configuration may affect the team’s performance efficiency. Using employing panel data methods, their research found that pay variation has a considerably harmful outcome on the team’s achievements. The conclusion is that a baseball team’s achievement in regard to wins does not appear to be connected with effectiveness. As stated in Team A’s second week research process paper some of the lowest ranking MBL organizations are a number of the most proficient. Also pay inequality does not connect with efficiency. Therefore, money generated by baseball teams is not essentially connected with baseball team effectiveness. On the other hand if judgment sampling had been in use it would not be as broad in range as random sampling could be. It could have a number of personal bias based on personal feelings toward a particular baseball team or yet a player or manager. Reliability and validity are important factors in the research to ensure that bias did not enter play. Reliability insist on the use of reliable data collection instruments and survey procedures: maintaining survey integrity, managing, processing, and analyzing survey data, and pre-testing data collection instruments intend to enhance consistency. Validity is the degree to which the survey data is important to the conclusion drawn and is adequately correct and inclusive to sustain the conclusion. Data Collection Example of top three highest salaries MLB teams data in tabular format: X1 | X2 | X3 | X4 | X5 | X6 | X7 | X8 | X9 | X10 | X11 | X12 | X13 | Team | League | Built | Size | Surface | Salary-millions | Wins | Attendance | Batting | ERA | HR | Error | SB | Boston | 1 | 1912 | 33871 | 0 | 123.5 | 95.0 | 2,847,798 | 0.281 | 4.74 | 199 | 109 | 45 | NY Yankees | 1 | 1923 | 57746 | 0 | 208.3 | 95.0 | 4,090,440 | 0.276 | 4.52 | 229 | 95 | 84 | NY Mets | 0 | 1964 | 55775 | 0 | 101.3 | 83.0 | 2, 827, 549 | 0.258 | 3.76 | 175 | 106 | 153 | | | | Example of all 30 MLB teams in graphical format: | Methods of collecting data can be from both primary and secondary sources. A primary source is information is obtainable firsthand by the researcher, for instance, an individual who is looking for the information and uses the Internet or a group selected by the researcher to explore sources for the information. Secondary sources are from information that has already been obtained and is currently existing data; these could be in the forms of company records, historical archives, analysis or publications. Some primary data is accessible by an unobtrusive process, a process that does not involve human interaction. This method can be a well-worn library book or journal, as this is an indication that this is a popular source of information because is it often used. Another method of unobtrusive material is vital statistics. Some secondary sources are internal records of an organization or external records such as articles, periodicals, census data, databases, and the media. Data collection can be in the form of interviews, surveys, electronic media interviews, observations, and testing. The methods used most often are interviews, surveys, and observance in obtaining data. Attendance at major league baseball games and the determining factors are weather, population, and economic issues will determine what the attendance will be. Questions for the problem matter would be is the stadium easily accessible, are there enough seats to compensate the attendees, and the opportunities to attend the function. The database for baseball informational statistics is extremely large, mostly because baseball does not change. Baseball fans keep in-depth records of the statistics involving the teams and their achievements. The attendance greatly resembles the efforts of the team because they show fewer attendees if they are playing at their home stadium or if they are falling behind in the divisional leaders. The won-lost percentage is the only significant variation that has an effect on attendance (Marcum & Greenstein, 1985). Quantitative methods are methods that collect information derived from a concept that will define the extent of the occurrence of concern. This may be a range of random participants or characteristics to influence an outcome on the variables selected. Three quantitative methods are experiments, observation, and surveys. Qualitative methods used for data collection are interviews, opinions, and document reviews. These methods are to generate an impact valuation to perceive and measure perceptions of people and how they would change in different variables. This method gives the opportunity for the research to change variables by adding or dropping practices. Possible ethical concerns with Major League Baseball and the statistical information gathered could present a leak in privacy or confidentiality. In a group setting the questions asked will need to be tactful and not blatant disrespect to the members of the groups. A researcher should conduct a more personal type of interview if they require personal information form their sources. They can tie the responses together in a report and protect the confidential information of each participant. Self-esteem and respect should be top priority for all subjects and beware of individual principles that could prejudice the study. In the major league baseball, if a team study consists of mostly one nationality, a survey of different nationalities preferences would bias the study because the team would not be aware of the preferences of the other nationalities. Safety among the participants should be of foremost concern to the researchers, asking questions that could put a subject in harm’s way or produce personal information of other team members would be unethical. Data collection is a major key in any research project. Making sure that data collected from reliable sources is important as well as making sure the information collected is pertinent to the research question. A researcher can collect data in many ways, and it is the responsibility of the researcher to discover which method work best for him or her. After gathering the data it will need to be displayed and that can be done in either a tabular or graphical format depending on how the researchers feel the information will best be displayed. With all the collecting and displaying done in research it is always important to ensure that the questions are answered.

References Avrutin, B. M., & Sommers, P. M. (2009, 9 September). Work Incentives and Salary Distributions in Major League Baseball. Atlantic Economic Journal, n.d.(n.d), 1-2. Doi:10.1007/s11293-007-0984-8 Data Collection Methods. (2001). Retrieved from www.people.uwec.edu/peircech/ResearchMethods/Data%20collection%20methods/DATA Jewell, R., & Molina, D. J. (2004). Productive Efficiency and Salary Distribution: The Case of US Major League Baseball. Scottish Journal of Political Economy, 51(1), 127-142. Retrieved from EBSCOhost. Lind, Marchal, and Wathen. (2008). Statistical techniques in business & economics, 13th edition. New York, NY: McGraw-Hill Tabular and graphical data Retrieved from https://ecampus.phoenix.edu/secure/aapd/ubam/res341/r4/DataSets/RES341r4MLB.htm Marcum, J. P., & Greenstein, T. N. (1985). Factors affecting attendance of major league baseball: II. A within season analysis. Sociology of Sport Journal, 2(4), 314-322 9p. Retrieved from ehis.ebscohost.com/eds/delivery?sid=db86d-6864-4371-8def-2f8e961f8228%40s Sampling definition. (n.d.). Retrieved from www.wordiq.com/definition/Statistical theory Sekaran, U. (2003). A skill-building approach. In Research methods for business (Chapter 10). Retrieved from https://ecampus.phoenix.edu/content/ebooklibrary/content/TOC.aspx

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