Executive Summary

Through our daily observations, we see that a considerable number of SIM students have begun using Apple Macintosh computers. This is despite the fact that SIM’s existing hardware infrastructure does not support the use of a Macbooks (or Macs for short).

This report sets out to investigate whether or not SIM’s Integrated Information Technology Services (IITS) department should seriously consider updating the university’s hardware to keep up with SIM students changing usage. A statistical analysis of our findings is conducted.

Based on anecdotal observations, we hypothesized that 30% of the school population use an Apple Macbook. We then carefully conducted an online survey of 51 SIM students, ensuring a stratified sampling which reflects the distribution of the university’s student population. After conducting an upper tailed one-sample z test, we obtained sufficient evidence to reject our null hypothesis.

Based on our proportionate sample, we found out that more than 30% of our school population use an Apple Macbook. The large proportion of students using Apple Macbooks warrant an initiative by IITS to equip and update the school infrastructure with Mac-friendly software and hardware. The preference for an Apple Macbook has transformed it from an exotic choice to a popular choice chosen by the school population. We recommend IITS to embark on a feasibility study immediately to update the school’s firmware to support the Mac platform

1. Introduction: The Problem

SIM's existing hardware infrastructure does not support the use of Macs. Students rely heavily on laptops to get their university course work done. Through our daily observations, SIM students are making the switch to using a Mac instead of a laptop with a Windows operating system. Those who use Macs instead of Windows face a lot of difficulties.

Seminar rooms in SIM do not cater to Macs. Existing Mac users have to buy additional add ons to connect to the university’s infrastructure. Courses such as Computer as an Analysis Tool and every course that requires a laptop for use in examinations need the SIM Exam Browser installed. However, the SIM Exam Browser is not compatible with the Mac operating system. The student must completely adjust his system to run the exam browser.

In order to connect to SIM’s wireless network laptops need to use the WLAN-Finder, which is a .exe file. There is no university support for Mac users to connect to the university’s Wi-Fi system. Students have to resort to student-led grassroots Mac communities for advice on Wi-Fi configuration. Project rooms in SIM’s library use a system called WE-Present to link up laptops to screens. This system is incompatible with Macs. Students who use Macs also have difficulty printing on the university network. This is a huge hindrance to Mac users.

Currently, students with Macs need to use loaned laptops from CIT or the bootcamp software. This is troublesome and labour intensive. Furthermore, installing boot camp software to run two operating systems decreases the efficacy of Macs considerably.

2. Hypothesis

We sought to find out, using a sample, SIM's population of mac users versus that of PC laptop users. Our group felt that over 30% of the population would be a large enough figure for CIT to start to provide additional infrastructural and service support for Macintosh users. As such, we hypothesized that the population proportion that use Mac laptops is equals to or less than 30%. If H0 is not rejected, then the population of Mac users is not large enough for CIT to do anything about. If H0 is rejected, then CIT should do something about the infrastructural and service support for Macintosh users. We will conduct a single tailed, one-sample z-test in which:

Null hypothesis, H0: P ≤ 0.3
Alternative hypothesis, H1: P > 0.3
Significance level: 0.05

3. Data Collection

3.1 Population and Sample

We will be using the SIM undergraduate student body as our population, as these are the primary beneficiaries of IITS services. Our sample includes participants across the various schools at SIM. It includes students from year 1 to year 5 from the School of london, School of Bufflo. In our sample, the number of participants chosen per school corresponds with the proportion of each school to the total population of the university. This allows us to receive a more accurate result. As far as possible, this ensures that all sections of the student body are represented in the sample.

Table 1. Date retrieved from the student portal Oasis depicts the current student population per school as follows.

School | Number of Students | Proportion of the Total Student Population (%) | SOL | 2790 | 0.41 approx. | SOB | 1086 | 0.16 approx. | SOT | 845 | 0.12 approx. | SSS | 1064 | 0.16 approx. | SCC | 562 | 0.08 approx. | STL | 506 | 0.07 approx. | Total | 6853 | 100 |

Table 2. shows the breakdown of the sample. The total sample size is 51.

School | Number of Participants | London | 25 | Psychology | 7 | Buffalo | 5 | UOL | 5 | Technology | 6 | Social science | 3 | 3.2 Measurement

We conducted an online survey where 3 questions were asked. These questions are depicted in Figure 1 below. The first measurement question was whether the survey participant used a Macbook or Windows laptop. The second and third questions were for demographical purposes.

Figure 1. Screenshots of online survey questions.

4. Results

After sampling 51 SIM students, the following results were obtained as depicted in the Stem and Leaf diagram below (Figure 2). The number 1 is used to denote survey participants who use Macbooks. The number 2 is used to denote survey participants who use Windows Laptops. Amongst our survery participants, 22 use a Macbook and 29 use a Windows Laptop. Figure 2: Stem and Leaf diagram of the survey results.

5. Hypothesis Testing

Analyzing the sample data, we calculate the standard deviation (σ) and compute the z-score test statistic (z), where n = 51, and p = sample proportion.

σ = sqrt [ P * (1-P) / n ] z = (p – P) / σ

Using PH stat, the values obtained are shown in Figure 3. Since population size is at least 10 times as big as sample size, each sample point can only result in just two possible outcomes and the sample includes at least 10 successes and 10 failures, the conditions are met for the hypothesis testing of a proportion. Also, since n = 51, is sufficiently large, the sample is approximately normal according to the Central Limit Theorem (CLT). No assumption is needed.

As such, the data provides sufficient evidence that the proportion of mac users in SIM are more than 30%.

Figure 3: Screenshot of PH stat result

6. Conclusion & Recommendations

We conclude that there are more Mac users than we actually perceived. The larger than expected minority should be served by IITS. The school’s infrastructure should be optimized for Mac users as the mac users are currently being put in a disadvantageous position which does not optimize their learning experience. We recommend that IITS invest in a feasibility study to ascertain the effects.