Qnt561
Data Analysis, Interpretation, and Conclusion, Part IV
Domingo Melchor, Ed Mendoza, Allen LaHeist, Noel Alba
University of Phoenix
MU11MBA07
QNT/561
Dr. Jyotirmay Deb, Ph.D.
Workshop/Week 4
July 21, 2012
Abstract
Part IV of the business research proposal paper is the analysis and interpretation of the data collected in Part III. This installment of the paper illustrates the hypothesis testing technique of analyzing data. It answers the questions raised in Part I about low attendance at the Charlotte Bobcats basketball team. It shows the interpretation of the result of the analysis. The paper concludes with lessons learned during the research and with recommendations to the Charlotte Bobcats management to solve their attendance dilemma.
Data Analysis, Interpretation, and Conclusion, Part IV
Team D organized the home-game attendance records and players’ statistics into sortable format for analysis. During the analysis process, the players’ statistics were deemed irrelevant to the objective of the research. The player attendance and winning records were expanded to six years of data to obtain larger population than the one-year numbers collected in Part III. The increase in population provided a larger sample size. It also provided more accurate data because it shows the sustained performance of the professional basketball teams through a six-year period.
Data Analysis: Hypothesis Testing
Team D uses the hypothesis testing technique to determine the effect of losing to low attendance (McClave, Benson, & Sinsich, 2011). The basis for the hypothesis is the research questions from Part I: Does losing record affect home-game attendance? Recall the dependent variable is home-game attendance of the Charlotte Bobcats and the independent variable is its losing records.
Three sets of samples were taken from the collected data. The first sample is random selection of 50 teams. The second is of the winning teams, those with winning
Domingo Melchor, Ed Mendoza, Allen LaHeist, Noel Alba
University of Phoenix
MU11MBA07
QNT/561
Dr. Jyotirmay Deb, Ph.D.
Workshop/Week 4
July 21, 2012
Abstract
Part IV of the business research proposal paper is the analysis and interpretation of the data collected in Part III. This installment of the paper illustrates the hypothesis testing technique of analyzing data. It answers the questions raised in Part I about low attendance at the Charlotte Bobcats basketball team. It shows the interpretation of the result of the analysis. The paper concludes with lessons learned during the research and with recommendations to the Charlotte Bobcats management to solve their attendance dilemma.
Data Analysis, Interpretation, and Conclusion, Part IV
Team D organized the home-game attendance records and players’ statistics into sortable format for analysis. During the analysis process, the players’ statistics were deemed irrelevant to the objective of the research. The player attendance and winning records were expanded to six years of data to obtain larger population than the one-year numbers collected in Part III. The increase in population provided a larger sample size. It also provided more accurate data because it shows the sustained performance of the professional basketball teams through a six-year period.
Data Analysis: Hypothesis Testing
Team D uses the hypothesis testing technique to determine the effect of losing to low attendance (McClave, Benson, & Sinsich, 2011). The basis for the hypothesis is the research questions from Part I: Does losing record affect home-game attendance? Recall the dependent variable is home-game attendance of the Charlotte Bobcats and the independent variable is its losing records.
Three sets of samples were taken from the collected data. The first sample is random selection of 50 teams. The second is of the winning teams, those with winning
References: McClave, J. T., Benson, P. G., & Sinsich, T. (2011). Statistics for Business and Economics (11th ed.). Retrieved from The University of Phoenix eBook Collection database.