# Ontario University Rankings

### Cynthia Yeh

## A little introduction

Rather than focusing on the programs I will be applying to (as they are all very different), I conducted my research based on the universities that I am considering. Therefore, the ranking of the universities will not necessarily reflect my top choice in terms of program, but which university campus meets my demands the best.

## Universities

## Raw Data & Weighting

*Note: All manipulated data is rounded to the nearest hundredth.*

## Manipulated Data & Reasoning

## Average Entering Grade

**Formula: (x/90)*10**

The average entering grade is weighted at 40% because universities usually look at grades to determine whether one is presented with an offer to the university program or not. In order to get into my ideal program(s) at the universities, I must keep my grades up for my senior year and knowing the average entering grades for my university choices will help me in setting a grade average goal for myself. The higher the average entering grade, the more I will need to work hard to achieve a higher overall average.

**I want my ideal school to have a rating of 10.**

As I aim to achieve an overall average of 90% for my senior year, 90% is the ideal entrance average for me. Also, as many schools' average entering grades are within the 80s range, achieving a 90% as my grade 12 average will give me a better chance in receiving an offer to the school. Since I want the school with an average of 90% to score the best and have a rating of 10, I need to create a formula that gives me 10 as the result when *x* is 90.

By dividing 90 by itself and multiplying the answer by 10, the product will be 10.

* (x/90)*10*

*= (90/90)*10*

*= 1*10*

*= 10*

Therefore, whichever university's manipulated average entering grade is closest to 10 is the ideal choice for me.

**Ranking:**

- Queen's
- Waterloo
- Western
- McMaster
- Toronto
- Wilfrid Laurier

## Tuition

**Formula: (7000-x)/100**

The tuitions for the universities are weighted at 20%. As both my parents work hard for their money, it would be ideal to attend a university where the cost is lower, so my parents will not have to pay as much.

**I want my ideal school to have a rating of 10.**

I subtracted the raw data (*x*) from 7000 and divided that by 100. I chose to subtract *x *from 7000 because by looking at the raw data, all of the tuition fees are in the six-thousand range, and by subtracting *x *from 7000, it allowed me to order the raw data by value - the larger the difference, the cheaper the university; the smaller the difference, the more expensive the university. In order to make the data easier to work with, I divided the difference by 100 to produce a smaller number.

Therefore, whichever university's manipulated tuition is closest to 10 is the ideal choice for me.

*Note: tuition does not include books & supplies, residence & meal plans, or any other personal expenses (fitness, clothing, entertainment, etc.)*

**Ranking:**

- Waterloo
- McMaster
- Queen's
- Wilfrid Laurier
- Western
- Toronto

## Total Number of Full-Time Students (Undergraduates + Graduates)

**Formula: 10-[(x-15000)/1000]**

The total number of full-time students is weighted at 20%, as it gives an accurate representation of the population of the university. I wish to attend a university that is not too large in terms of population, but also not too small.

**I want my ideal school to have a rating of 10.**

An approximate of 15,000 students would be the ideal for me. Since I want the school with the ideal population of 15,000 students to have a rating of 10, I need to create a formula that will give me the result of 10 when *x *is 15,000.

To find the difference between the total number of full-time students at a university and my ideal total of 15,000 students, I must subtract 15,000 from the raw data. As all of the data is greater than 15,000, this will work well.

* x-15000*

To generate a smaller number that will be easier to work with, I must divide the difference by 1000.

* (x-15000)/1000*

When *x *is 15,000, *(x-15,000)/1000 *will equal 0.

* (x-15000)/1000*

* = (15000-15000)/1000*

* = 0/1000*

* = 0*

However, I want *x *to equal 10 when it is 15,000. Therefore, I must subtract the quotient of the previous part of the formula from 10.

* 10-[(x-15000)/1000]*

* = **10-[(15000-15000)/1000]*

* = 10-(0/1000)*

* = 10-0*

* = 10*

Therefore, whichever university's manipulated total number of full-time students data is closest to 10 is the ideal choice for me.

**Ranking:**

- Wilfrid Laurier
- Queen's
- McMaster
- Waterloo
- Western
- Toronto

## Student/Faculty Ratio

**Formula: x/10**

The student/faculty ratio is weighted at 10% because it is not a criteria that is very important to me, but will definitely benefit me in my education.

**I want my ideal school to have a rating of 10.**

In many cases, when there is a larger student/faculty ratio, the students get to know their professor better and are more likely to receive letters of recommendation and connections that will benefit them in the future. In order to make the data easier to work with, I divided the raw data by 10 to produce a smaller number.

Therefore, whichever university's manipulated student/faculty ratio data is closest to 10 is the ideal choice for me.

**Ranking:**

- Wilfrid Laurier
- Waterloo
- Toronto
- Queen's
- Western
- McMaster

## Residence Space

**Formula: x/1000**

Residence space is weighted at 5% because this is not an important factor that I am considering while choosing the right university for me, as most universities have guaranteed residence spaces for first-years. However, if in case I am not able to afford (using my own money) an off-campus apartment for my second year, it would be nice to have a higher chance in getting a residence for my second year.

**I want my ideal school to have a rating of 10.**

The more residence spaces there are, the higher the chance there is for me getting a space for my second year. In order to make the data easier to work with, I divided the raw data by 1000 to produce a smaller number.

Therefore, whichever university's manipulated residence space data is closest to 10 is the ideal choice for me.

**Ranking:**

- Toronto
- Waterloo
- Western
- Queen's
- Wilfrid Laurier
- McMaster

## Proportion who Graduate

**Formula: x/10**

The proportion of students who graduate is weighted at 5% because this is not an important factor that I am considering while choosing the right university for me; I am fairly confident that I will graduate from university. However, it may be a confidence booster just to know how many of the students graduate, so I know how much chance I have to graduate from the school.

**I want my ideal school to have a rating of 10.**

The higher the percentage of students who graduate, the better chances I have to graduate. In order to make the data easier to work with, I divided the raw data by 10 to produce a smaller number.

Therefore, whichever university's manipulated percentage of students who graduate is closest to 10 is the ideal choice for me.

**Ranking:**

- Queen's
- Western
- Toronto
- McMaster
- Waterloo
- Wilfrid Laurier

## Results

**Ranking:**

**Wilfrid Laurier**- Queen's
- McMaster
- Waterloo
- Western
- Toronto

## Conclusion

By knowing that Wilfrid Laurier is the top university in this ranking as well as in my own heart, I am reassured that this is indeed the right university for me, and I will now try even harder to get accepted to it.

## Sources

- Maclean's 2013 Canadian Universities Guidebook
- Universities' Websites
- Maclean's Personalized University Ranking Tool