Chat with us, powered by LiveChat Descriptive Statistics and Data illustration:? In this section, the submission must summarize how the data was obtained (see chapter 1 of the text). G - Wridemy

Descriptive Statistics and Data illustration:? In this section, the submission must summarize how the data was obtained (see chapter 1 of the text). G

 

Submit a Word document formatted in APA style complete with cover and reference pages.  The reference page must have at least one entry:  the textbook. 

The submission must be a form Research Report with the following parts:

  1. Background information about the case:  The section must provide information about the people, places, operations, business, etc. and the research question or practical business challenges for which the current research will be used to provide a solution .  This section need not be long; up to two well written paragraphs are usually sufficient. 
  2. Descriptive Statistics and Data illustration:  In this section, the submission must summarize how the data was obtained (see chapter 1 of the text). Graphs and charts illustrating the main features of the data are also required – please see chapter 2 of the textbook.   Finally, a table of descriptive statistics accompanied by  description and explanations of the main features of the data are also required.
  3. Statistical Method:  This part of the submission must explain the main statistical method(s) used in the case.   What is the theory behind it? What are the working hypotheses (null and alternative, etc.), what main measures, statistics, or parameters etc.,  are to be estimated or calculated using the method; how does it measures or calculates these measures, statistics, or parameters?  Finally, this section must describe how the results of the statistical method are interpreted. That is, what is it about the results that would indicate that the working hypotheses or research questions are confirmed or rejected or perhaps need to be modified and tested again? 
  4. Results:  The actual results of the statistical method applied to the data are now presented in this section.  The section requires the student to describe the results and their theoretical interpretation based on the description of the method described in the previous section.
  5. Conclusion and Recommendation:  This section restates the statistical results and applies it to the business situation in the case.  It also makes practical recommendations about what steps the business in the case can take going forward based on the results of the statistical analysis.  The application and recommendation can take one or more of these general forms.
    1. The statistical results of the data analysis provided an answer(s) to the issues that the business is facing.  As a result specific policies or practical steps can be implemented in the business. 
    2.  The statistical results of the data analysis provided only partial answers.  More research and tests need to be done to come up with a more useful answers for the business situation.
    3. The statistical results did not provide any useful information for the challenges that a business(s) is facing.  Recommendations for conducting new research with new approaches, data, variables, etc. may be required. 
    4. Note:  there is always room for 'further research' since it is impossible for a single research case to answer every possible question. 

Note

  1. The textbook provides narratives, questions, or actual steps/questions for each case study.  While these are useful for conducting actual research, the submission must take the form of a research report and follow the above pattern.
  2. Consistent with the emphasis of this course on interpretation, an edited version of the answer key for the case study has been provided here Download edited version of the answer key for the case study has been provided here.  Students are required to use the information to enhance their understanding of the statistical methods and the results obtained.  

Case 15.1: Dynamic Scales, Inc.

The central issue in this case is the need to …. to accurately predict the … weight of trucks. If a “good” model can be developed, trucks determined to be within the acceptable weight limits will not be required to stop at the regular weigh stations.

Let

y =

Static weight

x1 =

Dynamic weight

x2 =

Truck speed

x3 =

Temperature

x4 =

moisture

The multiple regression information from Excel is given below:

Regression Analysis

Regression Statistics

Multiple R

0.883688864

R Square

Adjusted R Square

Standard Error

Observations

30

ANOVA

 

df

SS

MS

F

Significance F

Regression

4

Residual

25

Total

29

 

Coefficients

Standard Error

t Stat

P-value

 

Intercept

Front-Axle Dynamic Weight

Truck Speed

Temperature

Moisture

 

Note that only the slope coefficient for Front-Axle Dynamic Weight is significant. The other variables are not significant at any reasonable level of alpha as can be seen by looking at the p-value column. The overall model is …. and the adjusted R2 = ……

Students can use the stepwise regression feature of PhStat or XLSTAT to try to develop a better model. The results are as follows:

Stepwise Analysis

Table of Results for General Stepwise

Front-Axle Dynamic Weight entered.

 

df

SS

MS

F

Significance F

Regression

Residual

Total

 

Coefficients

Standard Error

t Stat

P-value

 

Intercept

Front-Axle Dynamic Weight

 

No other variables could be entered into the model. Stepwise ends.

This model is also significant and has an R2 of. The students might indicate that the company could want to explore other variables as possible independent variables.

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