Securing Higher Grades Costing Your Pocket? Book Your Assignment at The Lowest Price Now!
Add File

Error goes here

Files Missing!

Please upload all relevant files for quick & complete assistance.

Guaranteed Higher Grade!

BUS1BAN Analysing Business Data

tag 0 Download 0 Pages / 0 Words tag 21-06-2022
  • Course Code: BUS1BAN
  • University: La Trobe University
    icon is not sponsored or endorsed by this college or university

  • Country: Australia



The following research aims to take an insight into the Smartphone demands at La Trobe University. The research is driven by the high competition among Smartphone suppliers who offer a wide variety of Smartphone in the market (Cecere et al., 2015). The research targeted students at La Trobe University who are enrolled into BUS1BAN. A questionnaire was developed to capture the data for analysis. The questionnaire contained both open ended and close ended questions. After the development of the questionnaires, students were asked to answer to an online survey. From the data collected from the survey, a random sample of 100 participants was selected. The sample, selected through excel functions is aimed to represent the whole population and ensure that the analysis is efficient and effective (Candes & Wakin, 2008).

Data Analysis

Section A: Basic Analysis

1. Proportions of male and female

From the data selected number of males was 54 while the number of females was 46. Thus, the proportion of males in the sample was 0.54 while the proportion of females in the data was 0.46.

2. Average monthly bill

Table 1: Average Bills and Earnings

From table 1, it is observed that monthly average bill of males was $62.78. On the other hand, the average monthly bill of females was $71.78. 

3. Average monthly earning

From table 1, it is observed that the monthly average earnings of males are

1,234.70 dollars while the average monthly earnings of female students are 1,114.21 dollars.

To determine the relationship between two variables, a correlation analysis was carried out (Cohen et al., 2013).

Table 2: Correlation analysis

From table 2, it can be seen that earnings and money spent have a relationship. Though the relationship is positive, it is weak since its correlation is 0.35 (Podobnik & Stanley, 2008).

4. Market share

Figure 1: Male market share

Figure 1 shows that Apple is the leading Smartphone with a market share of 65% with Samsung having 16% and other Smartphone with 16%. On the other hand, LG has the least market share with 4%.

Figure 2: Female market share

Figure 2 shows that Apple is also the leading Smartphone with a market share of 81% with Samsung having 15%. On the other hand, LG and other Smartphone have the least market share with 2% each.

Section B: Intermediate Market Analysis.

5. The table below was developed to determine the choice of mobile phone and the earnings of students. The earnings of students were classified between the lower class ($0-$1300), middle class ($1,301-$2,600), and upper class ($2,601-$4,900).

Table 3: distribution of mobile phones according to monthly earnings

Determination of earnings of students and choice of the mobile relationship was determined through the use of a chi-square test (Balakrishnan et al., 2013).


            H0: students earnings and choice of mobile is independent

            H1: students earnings and choice of mobile is dependent

Table 4: Chi-square derivation

Table 4 shows how the chi-square of 3.108 was derived. From the chi-square distribution tables, at 0.05 probability level and 4 degrees of freedom, the critical value is 9.488. Since 3.108 is less than 9.488, we choose to accept the null hypothesis (Satorra & Bentler, 2001). Thus, the relationship between students' earnings and choice of mobile phones does not exist. On the other hand, we can conclude that earners of high-income do not use different phones than middle and low-income earners.

6. Figure 3: Samsung market share discount trend
From the trend line in figure 3, it can be observed that the Samsung market share, in relation to Apple, increases with a Samsung discount offering.
7. Figure 4: Samsung market share discount trend with regards to gender

A similar trend can be observed with the market share and discount connection across gender where the Samsung market share increases with increase in the discount factor.

Section C: Advance Scenarios

8. a. The 95% interval estimate for selecting a female from the 2017 BUS1BAN is:

SE = 0.0498397

Z-value for 95% confidence level = 1.96

Thus, 0.46± (1.96*0.0498397) = 0.3623/0.5577

Thus, the probability of selecting a female is between 36.23% and 55.77%.

On the other hand, the 95% interval estimates for selecting a male:

SE = 0.04984

Thus, 0.54± (1.96*0.04984) = 0.4423/0.6377

Thus, the probability of selecting a male is between 44.23% and 63.77%.

b. The probability of selecting a student using other Smartphone is:

SE = 0.0286

Z-value for 99% confidence level = 2.576

Thus, 0.09± (2.576*0.0286) = 0.01633/0.16367

Thus, the probability of selecting a student using other Smartphone is between 1.633% and 16.367%.

9. The sample average monthly earning of male and female students is 1179.27 dollars with a standard deviation of 836.96 dollars. Thus, the average monthly earning of female and male La Trobe students is given by:

Z-value for 99% confidence interval = 2.576

Thus, 1179.27± (2.576*2.57) = 1172.65/1185.89

Therefore, the average monthly earning is between $1,172.65 and $1,185.89.

10. To test the claim that the US iPhone market share is more than 40%, the following is done:

H0: P?>p

H1: P?≤p

Z = (p-p?)/√ (p*q)/n

    = (0.4-0.72)/√ (0.72*0.28/100) = -7.127

P value of -7.127 is 0.00001

The result is significant at 0.05, 0.1, and 0.001. Thus, we choose to accept the null hypothesis and conclude that the US market survey claim is also true for La Trobe students (Aczel & Sounderpandian, 200).

 Summary and Discussion

From the research analysis, it has been seen that the females tend to spend more though they have a smaller average monthly earning compared to the males. Regardless of the gender, Apple is the leader in the market with more than 65% market share in both gender scenarios.

On the other hand, there is no relationship between the student's earnings and the type of mobile phone used. The competitive advantage of Samsung is based on the discount offered. The market survey carried out for the US market share has also been proved that it can be used for La Trobe students.

The sampling method used in the research was a random sampling. Thus, it represents the whole population (Britton et al., 2006). To make the research more efficient, the researcher can opt to increase the sample size to make it more representative of the whole population.


Aczel, A. D., & Sounderpandian, J. (2002). Complete business statistics (Vol. 1). McGraw-Hill/Irwin.

Balakrishnan, N., Voinov, V., & Nikulin, M. S. (2013). Chi-squared goodness of fit tests with applications. Academic Press.

Britton, T., Deijfen, M., & Martin-Löf, A. (2006). Generating simple random graphs with prescribed degree distribution. Journal of Statistical Physics, 124(6), pp.1377-1397.

Candès, E. J., & Wakin, M. B. (2008). An introduction to compressive sampling. IEEE signal processing magazine, 25(2), pp.21-30.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. Routledge.

Cecere, G., Corrocher, N., & Battaglia, R. D. (2015). Innovation and competition in the smartphone industry: Is there a dominant design?. Telecommunications Policy, 39(3), pp.162-175.

Podobnik, B., & Stanley, H. E. (2008). Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series. Physical review letters, 100(8), 084102.

Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507-514.

Download Sample Now

Earn back the money you have spent on the downloaded sample by uploading a unique assignment/study material/research material you have. After we assess the authenticity of the uploaded content, you will get 100% money back in your wallet within 7 days.

Unique Document

Under Evaluation

Get Money
into Your Wallet

Total 0 pages

Cite This Work

To export a reference to this article please select a referencing stye below:

My Assignment Help. (2022). Analysing Business Data. Retrieved from

My Assignment Help (2022) Analysing Business Data [Online]. Available from:
[Accessed 06 October 2022].

My Assignment Help. 'Analysing Business Data' (My Assignment Help, 2022) <> accessed 06 October 2022.

My Assignment Help. Analysing Business Data [Internet]. My Assignment Help. 2022 [cited 06 October 2022]. Available from:

Stuck on Any Question

Our best expert will help you with the answer of your question with best explanation.

We will use e-mail only for:

arrow Communication regarding your orders

arrow To send you invoices, and other billing info

arrow To provide you with information of offers and other benefits

250 words
Error goes here

Error goes here

Files Missing!

Please upload all relevant files for quick & complete assistance.

We Can Help!

Get top notch assistance from our best tutors !
Excel in your academics & career in one easy click!


Other Samples

Content Removal Request

If you are the original writer of this content and no longer wish to have your work published on then please raise the content removal request.


5% Cashback

On APP - grab it while it lasts!

Download app now (or) Scan the QR code

*Offer eligible for first 3 orders ordered through app!

callback request mobile
Have any Query?