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HI6007 Statistics for Business Decisions

Assessment Task – Tutorial Questions

Unit Code:  HI6007

Unit Name: Statistics for Business Decisions

Assignment: Tutorial Questions Assignment 

Weighting:  50%

Purpose: This assignment is designed to assess your level of knowledge of the key topics covered in this unit

Unit Learning Outcomes Assessed.: 

  1. Understand appropriate business research methodologies and how to apply them to support decision-making process.
  2. Understand various qualitative and quantitative research methodologies and techniques.
  3. Explain how statistical techniques can solve business problems;
  4. Identify and evaluate valid statistical techniques in a given scenario to solve business problems;
  5. Explain and justify the results of a statistical analysis in the context of critical reasoning for a business problem solving
  6. Apply statistical knowledge to summarize data graphically and statistically, either manually or via a computer package;
  7. Justify and interpret statistical/analytical scenarios that best fits business solution;
  8. Explain and justify value and limitations of the statistical techniques to business decision making and;
  9. Explain how statistical techniques can be used in research and trade publication

Description: Each week students were provided with three tutorial questions of varying degrees of difficulty.  The tutorial questions are available in the Tutorial Folder, for each week, on Blackboard. The interactive tutorials are designed to assist students with the process, skills and knowledge to answer the provided tutorial questions.  Your task is to answer a selection of tutorial question for weeks 1 to 11 inclusive and submit these answers in a single document.

The questions to be answered are;

Question 1 (7 marks) 

  1. With your own words, using relevant examples briefly define types of probability assigning methods (3 marks)
  2. Transport trade association conducted a survey of their members to determine what they felt were the important issues to be discussed with the management. The survey results showed that 74% felt that the job security was the important issue, while 65% felt that salary increment was an important issue. Of those who felt salary increment was an important issue, 60% also felt that job security was an important issue.
    1. What percentage of the members felt that both job security and salary increment were important? (2 marks)
    2. What percentage of the members felt that at least one of these two issues was important? (2 marks)

Question 2 (7 marks)  

Annual food consumption survey shows that number of instant food meals consumed per month by university students is normally distributed with a mean of 10 and a standard deviation of 3. 

  1. Calculate the proportion of students consume more than 12 instant meals per month?
  2. Estimate the probability that in a random sample of 25 students’ more than 275 instant meals are consumed.

Question 3 (11 marks)

D Dax limited installed a new safety equipment in order to reduce the number of person hours lost as a result of industrial accident. In a test to of the effectiveness of the equipment, a random sample of 50 departments was chosen. The number of person- hours lost in the month prior to and the month after the installation of the safety equipment was recorded. The percentage change was calculated and recorded. Assume that the population standard deviation is 5 and sample mean is -1.2. Can we infer at the 10% significance level that the new safety equipment is effective? 

You are required to 

  1. Formulate hypotheses                                                                                    (3 marks)
  2. Decide the suitable test statistics and justify your selection.                       (1 mark)
  3. Calculate the value of the relevant test statistics and identify the P value (3 marks)
  4. Based on the test statistics in part (III), decide the decision criteria. (2 marks)
  5. Make the final conclusion based on the analysis.                 (2 marks)  

Question 4 (11 marks) 

The table below shows data on research to examine the perception of business ethics among 3 groups of employees (higher score indicates higher ethical values). 

A

B

C

6

5

6

5

5

7

4

4

6

5

4

5

6

5

6

4

4

6

5

5

6

4

6

6

6

5

4

5

6

5

  1. State the null and alternative hypothesis for single factor ANOVA to test for any significant difference in the perception among three groups. (1 marks)
  2. State the decision rule at 5% significance level.                                                           (2 marks)
  3. Calculate the test statistic.                                                                                                      (6 marks) 
  4. Based on the calculated test statistics decide whether any significant difference in the mean price of gasoline for three bands. (2 marks)

Note: No excel ANOVA output allowed. Students need to show all the steps in calculations. 

Question 5 (7 marks) 

Relax mortgage has gathered following data to examine the relationship between housing starts and mortgage interest rate. 

Interest rate

3.5

3.0

2.8

3.6

2.75

3.4

3.12

2.86

3.02

2.6

3.3

Housing starts

100

120

150

130

170

135

130

185

127

190

96

You are required to;

  1. Derive the regression equation (3 marks)
  2. Estimate the no of housing starts if mortgage interest rate is 2.5% (2 marks) 
  • Calculate and interpret the correlation between interest rate and no of housing starts. (2 marks)

Question 6   (7 marks) 

D& T LTD marketing team needed more information about the effectiveness of their 3 main mode of advertising.  To determine which type is the most effective, the manager collected one week’s data from 25 randomly selected stores. For each store, the following variables were recorded:

Weekly gross sales 

Weekly expenditure on direct mailing (Direct)

Weekly expenditure on newspaper advertising (Newspaper)

Weekly expenditure on television commercials (Television)

Following is the regression output based on the above-mentioned data.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.442

R Square

A

Adjusted R Square

0.080

Standard Error

2.587

Observations

25

ANOVA                              

 
 

Df

 

SS

MS

F

Significance F

Regression

 

B

34.1036

E

F

0.1979

Residual

 

21

D

6.6933

   

Total

 

C

174.6631  

     
 

Coefficients

 

Standard Error

t Stat

Pvalue

Lower 95%

Intercept                                    12.31            4.70         2.62        0.02

2.54

 

Direct                                           0.57           1.72             H        0.74

-3.01

 

Newspaper                                   3.32           1.54         2.16        0.04

0.12

 

Television                                        G            1.96         0.37        0.71

-3.34

 

a. Complete the missing entries from A to H in this output  

 

     (2 marks)

b. Assess the independent variables significance at 5% level 

 

     (3 marks)

c. Does the model is significant at 5% level?                                

 

     (2 marks) 

FORMULA SHEET

Location of the pth percentile: 

𝐿𝑝= 𝑝 (𝑛+1)

100

IQR = Q3 – Q1

Expected value of a discrete random variable

𝐸

Variance of a discrete random variable

π‘‰π‘Žπ‘Ÿ

Z and t formulas:

π‘₯−πœ‡ Μ… πœ‡ 𝑝π‘₯Μ…πœ‡ 𝑍 =  π‘ 𝑍 𝑑  π‘ 

πœŽπ‘π‘ž

𝑛

Confidence intervals

Mean:

𝑠

π‘₯Μ…  

Μ‚

𝑝̂  

𝑧𝛼2/2 𝑝 π‘ž

𝑛 = 𝐡2                      

Time Series Regression 

𝑏

𝑏0 = π‘Œ − 𝑏1𝑑

𝑇𝑑 = 𝑏0 + 𝑏1𝑑

 ANOVA:

𝑆𝑆𝑇𝑅

 MSTR

                       π‘˜                                             2

 SSTR = ∑ 𝑛𝑗(π‘₯𝑗̅ − π‘₯ΜΏ)

                      𝑗=1

π‘˜

 SSE = ∑(𝑛𝑗 − 1)𝑠𝑗2

𝑗=1

Simple Linear Regression:

  Μ‚𝑦 = 𝑏0 + 𝑏1π‘₯

                    ∑(π‘₯𝑖 − π‘₯Μ…)(𝑦𝑖 − 𝑦̅)

       π‘1 =   ∑(π‘₯𝑖 − π‘₯Μ…)2 SSE

  MSE =  

𝑛𝑇 − π‘˜

π‘˜        𝑛𝑗

2  SST = ∑ ∑(π‘₯𝑖𝑗 − π‘₯ΜΏ)

𝑗=1 𝑖=1

 F = MSTR / MSE

            𝑏0 = 𝑦̅ − 𝑏1π‘₯Μ…

    SST    =    SSR    +    SSE

SSE = ∑(𝑦𝑖 − 𝑦̂𝑖)2                                  SST = ∑(𝑦𝑖 − 𝑦̅)2

SSR= ∑(𝑦̂𝑖 − 𝑦̅)2

Coefficient of determination 

     R2= SSR/SST                                                             

Correlation coefficient

 π‘Œ

π‘Ÿ      or            π‘Ÿ

R2 = (π‘Ÿπ‘₯𝑦 )2

π‘Ÿπ‘₯𝑦 = (sign of 𝑏1) Coefficient of Determination

Testing for Significance 

 s  = MSE = SSE/(n  2)                      s =  

  π‘ π‘ 𝑠                           Μ…                                              𝑑 = 𝑠𝑏𝑏11    F = MSTR / MSE

 MSR = SSR/k-1                 MSE = SSE/n-k

Confidence Interval for β1

𝑏1 ± 𝑑𝛼/2𝑠𝑏1

Multiple Regression:

 y =  + x + x +. . . + x + ο₯

              0          1 1          2 2                      p p

 π‘¦Μ‚ = b + b x + b x + . . . + b x

          0        1   1         2 2                      p p

      2                                                  2)     𝑛     

   π‘…π‘Ž        = 1 − (1 − 𝑅

𝑛

R2 = SSR/SST

\F distribution

Submission Directions

The assignment will be submitted via Blackboard.  Each student will be permitted only ONE submission to Blackboard.  You need to ensure that the document submitted is the correct one.

Academic Integrity

Holmes Institute is committed to ensuring and upholding Academic Integrity, as Academic Integrity is integral to maintaining academic quality and the reputation of Holmes’ graduates. Accordingly, all assessment tasks need to comply with academic integrity guidelines.  Table 1 identifies the six categories of Academic Integrity breaches.  If you have any questions about Academic Integrity issues related to your assessment tasks, please consult your lecturer or tutor for relevant referencing guidelines and support resources.  Many of these resources can also be found through the Study Skills link on Blackboard.  

Academic Integrity breaches are a serious offence punishable by penalties that may range from deduction of marks, failure of the assessment task or unit involved, suspension of course enrolment, or cancellation of course enrolment.

Table 1: Six categories of Academic Integrity breaches

Plagiarism

Reproducing the work of someone else without attribution. When a student submits their own work on multiple occasions this is known as self-plagiarism.

Collusion

Working with one or more other individuals to complete an assignment, in a way that is not authorised.

Copying

Reproducing and submitting the work of another student, with or without their knowledge. If a student fails to take reasonable precautions to prevent their own original work from being copied, this may also be considered an offence. 

Impersonation

Falsely presenting oneself, or engaging someone else to present as oneself, in an in-person examination.

Contract cheating

Contracting a third party to complete an assessment task, generally in exchange for money or other manner of payment.

Data fabrication and falsification

Manipulating or inventing data with the intent of supporting false conclusions, including manipulating images.

Source: INQAAHE, 2020 

If any words or ideas used the assignment submission do not represent your original words or ideas, you must cite all relevant sources and make clear the extent to which such sources were used. 

In addition, written assignments that are similar or identical to those of another student is also a violation of the Holmes Institute’s Academic Conduct and Integrity policy. The consequence for a violation of this policy can incur a range of penalties varying from a 50% penalty through suspension of enrolment.  The penalty would be dependent on the extent of academic misconduct and your history of academic misconduct issues.  

All assessments will be automatically submitted to SelfAssign to assess their originality.

Further Information: 

For further information and additional learning resources please refer to your Discussion Board for the unit.

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