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Use the same business problem/opportunity and research variable you wrote about in Week 3.Remember: Do not actually collect any data; think hypothetically.Write a 700- to 1,050-word summary in which y
Use the same business problem/opportunity and research variable you wrote about in Week 3.
Remember: Do not actually collect any data; think hypothetically.
Write a 700- to 1,050-word summary in which you:
- Identify the types of descriptive statistics that might be best for summarizing the data, if you were to collect a sample.
- Apply the types of inferential statistics that might be best for analyzing the data, if you were to collect a sample.
- Analyze the role probability or trend analysis might play in helping address the business problem.
- Analyze the role that linear regression for trend analysis might play in helping address the business problem.
- Analyze the role that a time series might play in helping address the business problem.
Format your paper consistent with APA guidelines using the template at right.
HERES THE WORK FROM LAST WEEK......
Business Research Report Proposal
Business Research Topic:
The manufacturing industrial company is selected study of the different variables regarding the production of the manufacturing company. The management team of the company wants to analyze the data for the study of the overhead costs in the company’s department regarding the production division. The manager want to find out the relationship between the overhead costs and other related variables such as direct labor hours, indirect labor hours, number of machine hours etc. For this purpose, the manager wants to collect the data for the given variables and then analyze this data for getting conclusions. Manager wants to develop the regression equation for the future estimation purpose. By using the different statistical methods and techniques, the manager wants to analyze the data for the overhead costs and other related variables for checking some claims. Let us see this research proposal in detail given as below:
Research Questions:
It is very important to establish the research questions or problems for any business study to find out the conclusions for the different claims. For this business research proposal, the research questions for the purpose of the data analysis are summarized as below:
a) To find out the mean values for the overhead costs and other related variables like direct labor hours, indirect labor hours, machine work hours, etc.
b) To find out the relationship between the overhead costs and other related variable
c) To develop the regression equation for the estimation of the overhead costs for the production for future use
d) To test the claim regarding the equality of the mean overhead costs for the different timings.
Research Methodology:
The use of appropriate research methodology is very important for any data analysis of the research. If the research methodology is not appropriate or proper, the results or conclusions will not be appropriate or proper. For this research proposal, we have to study the data analysis for the variables such as overhead costs; the number of machine hours worked, the number of direct labor hours and the number of indirect labor workers. The first step in the research methodology is the data collection for the variables under study. The data is collected for the variables overhead costs, the number of machine hours worked the number of direct labor hours and the number of indirect labor workers. After the data collection process, the use of descriptive statistics is very essential due to finding answers to research questions. To checking the relationship between the different variables is needed for answering research question. For this purpose, we can use the scatter diagram to check whether the linear relationship exists between the given variables or not. Other than this diagrammatic figure, we can use the correlation coefficient to find the extent of the linear relationship exists between the given two variables. To find a regression equation is important for the future estimation of the overhead costs. For this purpose, the use of the regression analysis is useful. To checking the claim whether the average overhead costs are same or not for the given five years, the use of inferential statistics or testing of hypothesis is useful. Here, the one way analysis of variance is useful to checking the claim regarding the equality of average overhead costs for the given five years.
Data collection:
The data is collected for the variables overhead costs, the number of machine hours worked the number of direct labor hours and the number of indirect labor workers. Data is collected for the 60 months or five years for the variables overhead costs, the number of machine hours worked the number of direct labor hours and the number of indirect labor workers. Overhead costs are given in $.
Data analysis:
For the data analysis for the variables overhead costs, the number of machine hours worked the number of direct labor hours and the number of indirect labor workers, the use of descriptive statistics is very essential to getting the overall idea about the data and its nature. The descriptive statistics such as mean, standard deviation, range, etc. Should be collected for the variables overhead costs, the number of machine hours worked the number of direct labor hours and the number of indirect labor workers. To finding the correlation coefficient is important due to finding the relationship between the different variables such as overhead costs, the number of machine hours worked, the number of direct labor hours and the number of indirect labor workers. Also, the use of scatter diagram between the pairs of the variables from overhead costs, the number of machine hours worked the number of direct labor hours and the number of indirect labor workers is useful for getting the idea for the relationship. The use of one way analysis of variance is useful for checking the claim that the average overhead costs for the given five years are same or not. By using the p-value for the ANOVA table, the decision would be taken for rejecting or do not rejecting the claim or null hypothesis. The use of regression analysis is useful for finding the regression equation for the purpose of estimating the values of overhead costs based on the variables overhead costs, the number of machine hours worked the number of direct labor hours and the number of indirect labor workers.
Expected Research Outcomes:
1) The average values for the variables overhead costs, the number of machine hours worked the number of direct labor hours and the number of indirect labor workers should be obtained for this study.
2) Correlation coefficient between the different pairs from the variables overhead costs, the number of machine hours worked the number of direct labor hours and the number of indirect labor workers should be obtained for checking the relationship between the different pairs of variables.
3) The results for the claim whether the average overhead costs is same for given five years or not should be obtained from the test.
References:
• David Freedman, Robert Pisani, Roger Purves, Statistics, 3rd ed., W. W. Norton & Company, 1997.
• Morris H. DeGroot, Mark J. Schervish Probability and Statistics, 3rd ed., Addison Wesley, 2001.
• Leonard J. Savage, The Foundations of Statistics, 2nd ed., Dover Publications, Inc. New York, 1972.
• Robert V. Hogg, Allen T. Craig, Joseph W. McKean, An Introduction to Mathematical Statistics, 6th ed., Prentice Hall, 2004.
• George Casella, Roger L. Berger, Statistical Inference, 2nd ed., Duxbury Press, 2001.
• David R. Cox, D. V. Hinkley, Theoretical Statistics, Chapman & Hall/CRC, 1979.
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Statistics NMinimumMaximumSumMeanStd DeviationOverhead **** ** $602106007994003069750051162500190989644Number of ******* ***** ****************************************************** ** ****** ****** ************************************************** ** ******** labour ************************************* * **************************************************** **** ** $Number of ******* hours ************ ** ****** ****** *********** ** ******** labour *************** **** ** ******** ****************************** ************************************ ** ******* ***** ************* ***************************** (2-tailed)000 000037N60606060Number ** ****** ****** ************ ****************************** (2-tailed)000000 043N60606060Number ** ******** ****** ************** *************************** (2-tailed)043037043 N60606060** *********** is *********** ** *** *** ***** *********** *********** is *********** ** *** *** level ************************************************ ************************ CoefficientstSigBStd *********************************************** ** ******* ***** *************************** ** ****** ****** **************************** ** indirect ****** ************************** ********* ********* ******** **** ** ******************** cost ** ****** ** ************* ***************** ***************************************** ***************************************************************************
