Major Assignment BUS1BAN PDF

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Summary

This is an example of a HD BUS1BAN major assignment from Sem 2 2018. Recieved 18/20 for this component of the course.

This assignment will give you great direction when figuring out what answer will get you a HD for the assignment!

I achieved 83/100 for this unit....

Description

BUS1BAN Major Assignment Teacher’s Name Workshop Details (Time, day, room)

Students ID Number

Students Name

Student contribution* (%) e.g. 50% means the student will receive 50% of the marks awarded

Students Signature

*All group members are to exert an equal amount of effort on all questions of the assignment. Students should not divide sections. If a student has contributed to only some sections, the contribution of the student should be equal to the marks it carries. A student with less than 100% contribution will receive marks proportional to their contribution.

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An insight into student demand for smartphones at La Trobe University. Executive Summary I.

Introduction: (10% marks) This report provides a basic insight into the demand for smartphones from students at La Trobe University. 679 students took part in a survey, the data from which was used to devise this report. The participants in the survey were required to complete a questionnaire relating to gender, their average monthly phone bill, average monthly earnings, the type of smart phone (if any) they use, and finally, whether the incentive of a discount on another brand of phone would influence their decision in purchasing a new phone. Of the 679 students, a random sample of 100 was selected using the “=RAND()” function on Microsoft Excel. A sample of 55 Females and 45 Males was obtained. Descriptive and Inferential techniques were used to analyse the survey data as a mean of making assumptions about the wider total population surveyed.

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Data Analysis (75 marks):

II.

This section must answer the following specific questions.

Section A: Basic Analysis (25 marks) 1. Gender Proportion: (4 marks) A.

What proportion of the students in your sample are male and what proportion are female? Report your results in the following table. (1 mark)

Female Male

B.

Sample proportion 55 45

Use an appropriate chart to graphically display information in the table above. (2 marks)

Gender Proportions of Students in Sample

C.

45%

55%

Females

Males

Explanation. (1 mark)

There are 10% more females than males in the sample.

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2. Average Monthly Bill: (6 marks) A.

What is the average monthly bill of students by gender in your sample? Report your results in the following table. (2 marks) Female $64.13

Average Monthly Bill ($)

B.

Male $64.13

Use an appropriate chart to graphically display information in the table above. (2 marks)

Average Phone Bill by Gender 70

Average Phone Bill ($)

60 50 40 30

$64.13

$64.13

20 10 0 Females

Males

Gender

C.

Compare the average monthly bill of females and males. (2 marks)

The Average Monthly Phone Bill is the same for both Females and Males at $64.13.

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3. Earnings and money spent on mobile phone: (8 marks) A. What is the average monthly earning of students by gender in your sample? Report your results in the following table. (1 mark)

Average Monthly Earnings ($)

Female

Male

$1233.34

$1192.36

B. Is there any relationship between earning and money spent on mobile usage? Use an appropriate chart to illustrate your answer. (1 mark)

Relationship between Monthly Earnings ($) and Money Spent on Mobile Usage ($) 350

Monthly Mobile Usage ($)

300 250 200 ŷ = 51.26 + 0.0106x r² = 0.0426

150 100 50 0 0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

5500

MonthlyEarnings ($)

The trend line fitted to the scatterplot suggests a weak, positive linear relationship between Monthly Earnings and Monthly Mobile Phone Usage.

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C. Provide the following statistical measures to test the relationship between earning and money spent on mobile usage. (2 marks)

Covariance Coefficient of Correlation Coefficient of Determination Y-intercept Slope Least Squares Line

Female cov(x,y) = 11245.68

Male cov(x,y) = 4178.36

r = 0.296

r = 0.105

r2 = 0.0876 " 0 = 47.65 β β"1 =0.0134

r 2= 0.0111 β"0 = 56.62 "β1 =0.0063

ŷ = 47.6520 +0.0134x

ŷ = + 56.62 + 0.0063x

D. What do the statistics in part [C] tell you about the relationship between earning and money spent on mobile usage for males and females? Explain your results. (4 marks) Covariance The Covariance describes the direction of the relationship between two variables. A large, positive covariance indicates a positive relationship between x and y; i.e. as x increases, so does y. - Conversely, a large, negative covariance indicates a negative relationship between x and y; i.e. as x increases, y decreases. - A covariance near zero indicates no association between two variables. Given that a large positive covariance was calculated for both females and males (11245.68 and 4178.36 respectively), we can establish that a positive linear relationship exists between earnings and money spent on mobile usage for both genders. As earnings increases, so does mobile usage. Coefficient of Correlation The Coefficient of Correlation describes the strength of a linear relationship between two variables. - A Coefficient of Correlation of +1 indicates a strong positive correlation between two variables. - Contrarily, a Coefficient of Correlation of -1 indicates a strong negative correlation between two variables. - A Coefficient of Correlation of 0 or close to 0 indicates no correlation. Given the positive, albeit close to zero Coefficient of Correlation for both Females and Males (r = 0.296, and r = 0.105 respectively), we can establish that there is no correlation between earnings and money spent on mobile usage for both genders.

Coefficient of Determination The coefficient of determination measures the percentage of variation in variable y that is explained by variation in variable x. For females r2 = 0.0876, meaning that 8.76% of variation in mobile phone usage can be explained by variation in earnings. 91.24% of variation is unexplained and can be attributed to other factors. 6

For males r2 = 0.0111, meaning that 1.11% of variation in mobile phone usage can be explained by variation in earnings. 98.89% of variation is unexplained and can be attributed to other factors. Y-Intercept The y-intercept tells us the predicted value of y when x = 0. In this case, the y-intercept tells us that when a female’s monthly earnings = 0, their monthly mobile usage is predicted to be $47.65. For males, the y-intercept predicts that when earnings =0, their monthly mobile usage will be $56.62. Slope The slope tells us how much variable y will increase/decrease by for every 1-unit increase in variable x. For females, each additional dollar earned per month is predicted to increase monthly phone usage by $0.0134. For males, each additional dollar earned per month is predicted to increase monthly phone usage by $0.0063

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4. Market share of mobile phone brand: (7 marks) a. Complete the following cross classification tables (1 + 1 marks)

Apple

Gender

Basic mobile phone 0 0 0

Cross classification table by total relative frequency Brand Apple Samsung LG Do not Other Basic use smart mobile mobile phone phone phone 71.12% 13.33% 2.22% 0% 13.33% 0% Male 80% 12.73% 1.82% 0% 5.45% 0% Female 76% 13% 2% 0% 9% 0% Total

Total 45 55 100

Total 100% 100% 100%

E. Use an appropriate chart to graphically display the information above. (2 marks)

Mobile Phone Brand Market Share by Gender Market Share (%)

Gender

32 44 76

Male Female Total

Cross classification table by frequency Brand Samsung LG Do not Other use smart mobile phone phone 6 1 0 6 7 1 0 3 13 2 0 9

90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% Apple

Samsung

LG

Do not use Other smart Basic mobile phone phone mobile phone Brand

Male

Female

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F. Is there any difference in the market share of each mobile phone brand by gender? (3 marks) Females in the sample were more likely to own an Apple mobile phone than Males, with 80% of Females owning an Apple phone as opposed to 71.2% of Males. Females and Males were nearly equally as likely to own a Samsung mobile, with Samsung having a market share of 13.33% of females, and 13% of males in the sample. Males were more likely to own an “Other smart phone” than females, with this category accounting for 13.33% of the male market in the sample, as opposed to 5% of the female market. LG accounted for the lowest market share for both females and males, with only 1.82% of females and 2.22% of males owning a phone from the brand.

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Section B: Intermediate Market Analysis (25 marks) Relationship between the earning of students and choice of mobile phone: (9 marks) A.

Calculate the average income of students by brand. Report your results in the following tables. (1 mark)

Apple

Average income ($)

B.

1214.90

Frequency Brand Samsung LG Do not use mobile phone 1189.64 1478.333 -

Other smart phone

Basic mobile phone

1187.13

-

Use an appropriate chart to graphically display the information above and summarise the results. (1 mark)

Average Monthly Income ($) by Phone Brand 1600

Average Monthly Income ($)

5.

1400 1200 1000 800 600 400 200 0 Apple

Samsung

LG

Other smart phone

Brand

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C.

Divide income into three categories at your discretion (low, middle and high) and complete the following tables. (1 + 1 marks)

Apple

Income Level ($)

Low (0-1499) Middle (15003499) High (35005000) Total

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Cross classification table by frequency Brand Samsung LG Do not Other use smart mobile phone phone 10 2 0 8

Basic mobile phone 0

Total 71

23

3

0

0

1

0

27

2

0

0

0

0

0

2

76

13

2

0

9

0

100

Cross classification table by total relative frequency Brand Apple Samsung LG Do not Other Basic use smart mobile mobile phone phone phone 71.83% 14.08% 2.82% 0% 11.27% 0%

Income Level ($)

Low (0-1499) Middle 85.19% (15003499) 100% High (35005000) 76% Total

Total 100%

11.11%

0%

0%

3.7%

0%

100%

0%

0%

0%

0%

0%

100%

13%

2%

0%

9%

0%

100%

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D.

Employ an appropriate graph to compare the distribution of brand selection across the income groups. (2 marks)

Distribution of Brand Selection by Income Group Proportion (%)

100.00% 80.00% 60.00% 40.00% 20.00% 0.00% Low

Middle

High

Income Group ($) Apple

E.

Samsung

LG

Other smart phone

Provide an explanation on relationship between income and the choice of mobile phone. Is there a relationship? (3 marks)

There is no clear relationship between income and the choice of mobile phone. The bar graph above shows a vast majority students tend to prefer Apple irrespective of their income group. Samsung comes second in popularity across the low and middle income earners, though by a large margin. Although high income earners all owned an Apple phone, only two students from this income group were part of the sample and as such should be treated as outliers, rather than concluding that indeed as income increases so does the likelihood of owning an Apple phone.

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6. The effect of price on preference [Samsung versus Apple]: (10 marks) A.

iPhone and Samsung are two important players in the smartphone market who compete against each other. Samsung’s phones are generally sold cheaper than Apple’s smartphones. Complete the following table using the survey data responses (2 marks) Discount offered on Samsung Galaxy x 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Proportion of customers who said they will buy the latest Samsung Galaxy instead of the latest iPhone if the Galaxy was discounted. y 20% 20% 25% 21% 28% 31% 33% 36% 45% 52% 58%

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B.

Using Excel, produce a scatter plot to summarize the relationship between potential market share and proposed discount offered by Samsung on its latest Galaxy vis-à-vis the latest iPhone. (2 marks)

Proportion of customers who said they will buy the latest Samsung Galaxy instead of the latest iPhone if the Galaxy was discounted.

Relationship between Potential Market share and Proposed Discount offered by Samsung on its latest Galaxy vis-à-vis the latest iPhone.

70%

60%

50%

40% ŷ = 0.1477 + 0.7509x r² = 0.9064

30%

20%

10%

0% 0%

10%

20%

30%

40%

50%

60%

Discount offered on Samsung Galaxy

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C.

Complete the following table then interpret the statistics. (4 marks)

Covariance Coefficient of Correlation Coefficient of Determination Y-intercept Slope Least Squares Line

Statistic cov(x,y) = 0.0207 r = 0.952 2 r = 0.9064 "β0 = 0.1477 β"1 =0.7509

ŷ = 0.7509x + 0.1477

slope: For each additional discount offered (x), proportion of customers who said they’d purchase Samsung increases 0.7509. Covariance The positive covariance represents a positive association between Discount offered on Samsung Galaxy and Proportion of customers who said they will buy the latest Samsung Galaxy instead of the latest iPhone if the Galaxy was discounted Coefficient of Correlation The coefficient of correlation of 0.9520 suggests there is a strong, positive linear relationship between Discount offered on Samsung Galaxy and Proportion of customers who said they will buy the latest Samsung Galaxy instead of the latest iPhone if the Galaxy was discounted. Coefficient of Determination 90.64% of variation in Proportion of customers who said they will buy the latest Samsung Galaxy instead of the latest iPhone if the Galaxy was discounted is explained by variation in Discount offered on Samsung Galaxy. 9.36% of variation can be attributed to other variables. Y-Intercept When Discount offered on Samsung Galaxy = 0, the Proportion of customers who said they will buy the latest Samsung Galaxy instead of the latest iPhone if the Galaxy was discounted = 14.77% Slope For each additional 1% Discount offered on Samsung Galaxy, the Proportion of customers who said they will buy the latest Samsung Galaxy instead of the latest iPhone if the Galaxy was discounted increases by 0.7509%.

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D.

Using your answer to [A], [B] and [C], does Samsung’s market share, relative to Apple, increase or decrease with the discount offered by Samsung? Which customers are more loyal to their brand? (2 marks)

Ultimately, given the answers in parts A, B and C, Samsung’s market share does indeed increase with the discount offered relative to Apple, evidenced by the positive linear relationship between discount offered by Samsung (x) and , the Proportion of customers who said they will buy the latest Samsung Galaxy instead of the latest iPhone if the Galaxy was discounted. It is not possible to conclude which customers are more loyal to their brand as we are not aware of the statistics regarding if a discount was offered by Apple, would Samsung customers then switch to apple. I.e. the opposite of the recorded data. Despite this, when a 45% discount is offered on Samsung, more than half (52%) of Apple customers would switch to Samsung, allowing us to assume price is a key motivator when selecting a mobile phone rather than brand.

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7.

The effect of price on preference & gender [Samsung versus Apple]: (6 marks) Compare the discount and market-share relationship in question 6 across gender.

A. Complete the following table using the survey data responses (2 marks) Discount offered on Samsung Galaxy x 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Proportion of customers who said they will buy the latest Samsung Galaxy instead of the latest iPhone if the Galaxy was discounted Females Males yM yF 16.36% 24.44% 16.36% 24.44% 18.18% 33.33% 18.18% 24.44% 23.64% 33.33% 29.09% 33.33% 29.09% 37.78% 32.73% 40% 43.64% 46.67% 50.91% 53.33% 55.55% 62.22%

B. Using Excel, produce a scatter plot to summarize the relationship between potential market share of males and females, and proposed discount offered by Samsung on its latest Galaxy vis-à-vis the latest iPhone. (1 mark)

Potential Market Share

Relationship between Potential Market Share of Males and Females, and Proposed Discount offered by Samsung on its latest Galaxy vis-à-vis the latest iPhone 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% 0%

10%

20%

30%

40%

50%

60%

Proposed Discount Females

Males

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C. Complete the following table and note any differences between the statistics for females and males. (2 marks) Statistic Covariance Coefficient of Correlation Coefficient of Determination Y-intercept Slope Least Squares Line

Females cov(x,y) = 0.02225 r = 0.9637 r2 = 0.9378 β"0 = 0.1011 β"1 =0.0428 ŷ = = 0.0428x - 5E-05

Males cov(x,y) = 0.019 r = 0.9255 r2 = 0.8566 " 0 = 0.0777 β " 1 =0.041 β ŷ = = 0.041x + 0.0777

D. Using your answer to [A], [B] and [C], does Samsung’s market share, relative to Apple, increase or decrease across gender, with the discount offered by Samsung? Is there a difference in brand loyalty for females and males? (1 mark) Analysing the answers and comparing the statistics, Samsung’s market share, relative to Apple increases across both males and females with the discount offered. Relative to brand loyalty, there is a slight difference with females more loyal to their brand than males where this can be noted on the responsiveness to discount as each discount offered increases, less females switch from apple to Samsung.

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Section C: Advance scenarios (25 marks) 8.

Confidence intervals: (7 marks)

Suppose, you randomly selected a student from the 2017 BUS1BAN class.

a. How likely is it that the student will be a female and how likely is it that the student will be a male? (1 mark)

Sample proportion (𝑝$ )

Female 0.55

Male 0.45

Provide 95% interval estimates for each gender, show the confidence intervals graphically, and interpret your results.