HI6007 STATISTICS FOR BUSINESS TUTORIAL
Assessment Task – Tutorial Questions
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Unit Code: HI6007 Unit Name: Statistics for Business Decisions
Assignment: Tutorial Questions Assignment Due: week 13
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 the 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 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 fit 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 questions for weeks 1 to 11 inclusive and submit these answers in a single document.
The questions to be answered are;
Question 1: Week 2 Question 4 (7 Marks)
a. The following data shows the results for 20 students in one of the post-graduate unit.
42 66 67 71 78 62 61 76 71 67
61 64 61 54 83 63 68 69 81 53
Based on the information given you are required to
i. Compute the mean, median, and mode. (3 marks) ii. Compute the first and third quartiles. (1 mark) iii. Compute and interpret the 90th percentile. (1 mark)
b. In your own word, explain what is inferential statistics with relevant examples.
(2 marks)
HI6007 STATISTICS FOR BUSINESS TUTORIAL
Question 2: Week 3 Question 4, (7 Marks)
a. Holmes Institute conducted a survey about International Students in Melbourne. The survey results are given in the table below.
Age Group
Applied to more than 1 university
Yes No
23 and under 207 201
24-26 299 379
27-30 185 268
31-35 66 193
36 and over 51 169
i. Prepare a joint probability table (1 mark)
ii. Given that a student applied to more than 1 university, what is the probability that the student is 24-26 years old. (1 mark)
iii. Is the number of universities applied to independent of student age? Explain
(2 marks)
b. Assume, North Origano, is a country with the highest domestic violence cases (approximately
5 cases per 1000 families). Working with counselors, a researcher developed the following probability distribution for x= the number of new clients for counseling for 2021.
x f(x)
10 0.05
20 0.10
30 0.10
40 0.20
50 0.35
60 0.20
i. Compute the expected value and variance of x. (3 marks)
HI6007 STATISTICS FOR BUSINESS TUTORIAL
Question 3: Week 8 Question 3, (11 Marks)
According to the Annual Survey of Drug expenditure in country X, the annual expenditure for prescription drugs is $838 per person in the Northeast region of the country. A sample of 60 individuals in the Midwest shows a per person expenditure for prescription drugs of $745. Further, it is given that the population standard deviation of $300.
I. Formulate hypotheses for a test to determine whether the sample data support the conclusion that the population annual expenditure for prescription drugs per person is lower in the Midwest than in the Northeast and Identify whether it is a two-tail test or a one-tail test (Left or right tail). (3 marks)
II. Decide the suitable test statistics and justify your selection. (1 mark) III. Calculate the value of the relevant test statistics and identify the P-value (3 marks) IV. Based on the p-value in part (III), at 99% confidence level, decide the decision criteria. (1 mark) V. Make the final conclusion based on the analysis. (3 marks)
Question 4: Week 9 Question 2, (11 Marks)
The gasoline price often varies a great deal across different regions across country X. The following data show the price per gallon for regular gasoline for a random sample of the gasoline service station for three major brands of gasoline (A, B and C) located in 10 metropolitan areas across the country X.
A B C
3.77 3.83 3.78
3.72 3.83 3.87
3.87 3.85 3.89
3.76 3.77 3.79
3.83 3.84 3.87
3.85 3.84 3.87
3.93 4.04 3.99
3.79 3.78 3.79
3.78 3.84 3.79
3.81 3.84 3.86
a. State the null and alternative hypothesis for single-factor ANOVA to test for any significant difference in the mean price of gasoline for the three brands. (1 marks)
b. State the decision rule at a 5% significance level. (2 marks)
c. Calculate the test statistic. (6 marks)
d. 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: Week 11 Question 3, (7 Marks)
Dex Research Limited conducted research to investigate consumer characteristics that can be used to predict the amount charged by credit card users. The following multiple regression output is based on data collected by this research company on annual income, household size, and annual credit card charges for a sample if 50 consumers.
Regression Statistics
Multiple R 0.9086
R Square A Adjusted R Square 0.8181
Standard Error 398.0910
Observations B
ANOVA
df SS MS F Significance F
Regression 2 D E G 1.50876E-18
Residual C 7448393.148 F Total 49 42699148.82
Coefficients Standard Error t Stat P-value
Intercept 1304.9048 197.6548 6.6019 3.28664E-08
Income ($1000s) 33.1330 3.9679 H 7.68206E-11
Household Size 356.2959 33.2009 10.7315 3.12342E-14
a. Complete the missing entries from A to H in this output (4 marks) b. Estimate the annual credit card charges for a three-person household with an annual income of $40,000. (2 marks)
c. Did the estimated regression equation provide a good fit to the data? Explain (1 mark)
HI6007 STATISTICS FOR BUSINESS TUTORIAL
Question 6: Week 12 Question 2, (7 Marks)
Amex PLC has gathered the following information on the sales of face mask from April 2020 to
September 2020.
You are required to;
Month Sales ($)
April 17,000
May 18,000
June 19,500
July 22,000
August 21,000
September 23,000
a. Using linear trend equation forecast the sales of face masks for October 2020.
(5 marks)
b. Calculate the forecasted sales difference if you use a 3-period weighted moving average designed with the following weights: July 0.2, August 0.3, and September 0.5.
(2 marks)
Note: You need to show all the steps in your calculation. No excel files will be graded.
FORMULA SHEET
K = 1 + 3.3 log10 n
Summary Measures (n – sample size; N – Population size)
| �=1 |
𝜇 =
∑𝑁 � �
𝑁
�̅ =
∑𝑛 � �
| �=1 |
𝑛
� = �
𝑛
�2 = 1 ∑𝑛
(� − �)2
Or �2 = 1 [(∑𝑛
�2) − 𝑛�2]
𝑛−1
�=1 �
𝑛−1
�=1 �
𝑛 2
Or �2 = 1 [(∑𝑛
�2) − ( ∑� =1 � � ) ]
𝑛−1
�=1 � 𝑛
𝜎2 = 1 ∑𝑁
(� − µ)2 Or 𝜎2 = 1 [(∑𝑁
�2) − 𝑛µ2]
𝑁
�~ 𝑅 �𝑛𝑔𝑒
4
�=1 �
𝑁
�𝑉 = 𝜎
µ
�=1
�
�𝑣 = �
�
Location of the pth percentile:
| 𝐿𝑝= |
𝑝
(𝑛+1)
100
IQR = Q3 – Q1
The expected value of a discrete random variable
𝐸(�) = 𝜇 = ∑ � ∗ 𝑓(�)
The variance of a discrete random variable
𝑉��(�) = ∑(� − 𝜇)2 𝑓(�)
Z and t formulas:
| � = |
� = � − 𝜇
𝜎
� − 𝜇
𝜎
√𝑛
� = 𝑝̂− 𝑝
| � = |
��
√ 𝑛
� − 𝜇
𝑠
√𝑛
Confidence intervals
Mean:
� ± �𝛼/2
𝜎
√𝑛
� ± �𝛼/2
�
√𝑛
Proportion:
� �̂
� ± � 𝛼 √
2 𝑛
𝑛 =
2
| � � � |
𝛼/2
�2
Time Series Regression
| �=1 |
∑ 𝑛 [ ( � − � ) ( �� − � ) ]
�1 =
| �=1 |
∑𝑛 (� − �)2
�0 = � − �1�
�� = �0 + �1�
ANOVA:
MSTR =
����
𝑘 − 1
MSE =
SSE
𝑛𝑇 − 𝑘
� � 𝑛�
2 2
SSTR = ∑ 𝑛�(�� − �)
�=1
�
SSE = ∑(𝑛� − 1)��2
�=1
Simple Linear Regression:
̂� = �0 + �1�
∑( �� − � ) ( �� − �̅ )
SST = ∑ ∑(��� − �)
�=1 �=1
F = MSTR / MSE
�0 = �̅ − �1�
�1 =
∑(��
− �)2
SST = SSR + SSE
SSE = ∑(�� − �̂�)2 SST = ∑(�� − �̅)2
SSR= ∑(�̂� − �̅)2
Coefficient of determination
R2= SSR/SST
Correlation coefficient
∑(�− �)(�− �)
∑ ��−
∑ � ∑ �
� =
or
� = 𝑁
√(∑(�− �)2)(∑(�− �)2)
√(∑ �2− ( ∑ �) 2 )(∑ �2− ( ∑ � ) 2
| ) |
𝑁 𝑁
R2 = (��� )2
��� = (sign of �1)√Coefficient of Determination
Testing for Significance
| 2 |
s = MSE = SSE/(n 2) s = √MSE = √ SSE
𝑛−2
��1 =
�
√∑(�� − �)2
�1
� =
��1
F = MSTR / MSE
MSR = SSR/k-1 MSE = SSE/n-k
Confidence Interval for β1
�1 ± �𝛼/2��1
Multiple Regression:
y =
+ x
+ x
+ . . . + x +
0 1 1 2 2 p p
�̂ = b
+ b x
+ b x
+ . . . + b x
0 1 1
2 2 p p
𝑛 − 1
��2 = 1 − (1 − �2)
𝑛 − � − 1
R2 = SSR/SST
\F distribution
Submission Directions:
An 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.
HI6007 STATISTICS FOR BUSINESS TUTORIAL
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 offense 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.
HI6007 STATISTICS FOR BUSINESS TUTORIAL
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 authorized.
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 offense.
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.
HI6007 STATISTICS FOR BUSINESS TUTORIAL
Source: INQAAHE, 2020
If any words or ideas used in 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.
HI6007 STATISTICS FOR BUSINESS TUTORIAL
Further Information:
For further information and additional learning resources please refer to your Discussion Board for the unit.
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