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Professor:
For the 2009 Fall Term, Dr. Jonathan Yazinski taught this course, but will likely not be teaching it again, so I'll address content and tips for doing well.

Course Structure:
The 2008 class did not have assignments whereas the 2009 class did.
What you can definitely expect though is:
3 midterms, 1 final.
If you have assignments, the course structure might be similar to the following:
Assignments: ~10%
Exam 1: ~20%
Exam 2: ~20%
Exam 3: ~20%
Final: ~30%

Textbook:
The textbook used in 2008 and 2009 was "Finite Mathematics and Its Applications, 9th Edition" by Larry Goldstein.
I found the textbook useful in that it provided a wealth of problems, but not very informative. It is a worthwhile purchase, however, I didn't really learn from the textbook itself. Despite having many examples, the understanding, logic and thought process could stand to be improved upon. Oftentimes not having enough description regarding why certain things were done certain ways became really problematic when dealing with the material.

The best way to use the textbook is as mentioned above for practice. Do every question you can, because it builds up your understanding of the material just as seeing numerous problems of increasing difficulty worked out would - except with this text you do not have that advantage, so it's better to rely on your own skills.

Content:
Stats begins fairly easy (or it did with us) by going through sets and Venn Diagrams which most of us could handle.
An important tip is to ensure you do not dismiss these chapters as unimportant. If you have difficulties with the material here, you need to spend more time on it and seek extra help as it will not necessarily become any easier as you proceed.
Also, do not skip textbook problems. Venn diagrams will catch up to you later - mainly on midterms or the final. You don't want to have to use more complex statistical methods to solve a problem that could be done in 5 minutes with one of these.

Counting was where most of our class began to struggle. We had a good deal of difficulty approaching common real life problems in a different sense - that we had to solve them (such as rearranging books, or ordering dogs and cats).

We then moved on to Probability which got better when we relied on probability trees and a initially confusing but very helpful theorem known as Bayes Theorem. We also discussed probability distributions such as the binomial distribution and standard normal distribution.

From that we went onward to solving linear equations and matrices.

Doing Well:
I can say the same thing about all of these chapters.
They may seem easy, and something that can be put off till later but that's a mistake.
If you don't have a background in Data Management (and you aren't allowed to take this course if you do), you may find yourself having unusual amounts of difficulty with seemingly simple problems.

The most important thing you can do for yourself at that point is to continue working and make use of your instructor's office hours, go to tutorials and discuss concerns with your TA and take advantage of the Math Help Center.

To elaborate, in class you will be taught how to solve a matrix:
Eg:
| 9 4 5 | # |
| 6 8 1 | # |
| 4 3 7 | # |

by expressing it in this form:

| 1 0 0 | # |
| 0 1 0 | # |
| 0 0 1 | # |

Most students will initially manipulate the entire matrix to achieve the desired "identity matrix" (second picture). However, with a bit of practice and familiarity with the material you'll be able to solve it in 3 steps:

| 1 # # | # |
| 0 # # | # |
| 0 # # | # |

Where each # symbol represents a number that can be, but does not have to be the same as the other numbers in the grid.

Ensure you also do any practice tests your instructors release as they may be more likely to test you on that material than the material in your textbook.

Summary:
It is possible to do well in Stats but it is not a bird course, and will require a lot of effort. The course does move quickly, especially if they retain the 3 midterm structure. However, this does work to your favour if the final exam's content catches you off guard.

Your mark will also largely depend on the generosity of your professor (e.g. if assignments/the opportunity to earn extra credit are offered) but if you put in the work, you'll probably end up with a mark you're happy with.

In my opinion, I would have rather much taken data management in high school as I found stats 1L03 pretty challenging. I've always been a strong math student but for some reason could not grasp some of the concepts without struggling.

The example given in the above review about the matrix was definitely the easier of the topics, as was standard deviation, mean, variance etc, but I felt as though the prof was a little ineffective in teaching the class. As a person he was pretty interesting, really kind and always willing to help (to the point that I felt it consumed him maybe a little too much), but he seemed to be just too smart. I almost felt a little bad for him because I'm sure he was bored with the material he had to teach. He could explain the concepts better if you went to his office hours, but class moved at a pace faster than I was comfortable with.

As assumed from the complaints of the majority of my classmates it seemed as though everyone really struggled with the material. However, I have found that although I struggled with 1L03, I'm doing extremely well in Math 1M03, so I think it's just a different way of thinking. Also, I ended up with a 9 in stats 1L03, so you can always look forward to that ever-helpful curve at the end of the semester.