Transcription
Welcome to Stat 263, an introductory course in statistics offered at Queen's University in the summer of 2026. In this course, we're going to be looking at an introduction to modern statistics with all the necessary probability that's involved in that course. We'll begin by looking at simple probability models before looking at random variables and their distributions, after which we'll look at estimating properties of these distributions using data and then doing the same thing with hypothesis testing.
In order to complete the course, you'll need access to the free online textbook, which is available at the URL on screen. You'll also need a calculator that is capable of doing calculations with the normal distribution and some spreadsheet software like Microsoft Excel or Google Sheets.
You'll be graded in this course in four different ways. The first is through the weekly WebWork assignments that'll be available through ONQ. These are mainly for completion to ensure that you're getting enough practice with the material. The second is through the bi-weekly assignments, which will be submitted through Crowdmark. When new assignments are available, you get a new email through Crowdmark mailer, which will access the assignments and the submission page. The third way is through the three term tests, which will occur at the ends of week three, six, and nine. More information about these tests will be available on Q as we get closer to those dates. And the final way is through the final exam, which can be completed either online or in person at Queen's University. More information on that will be available as we get closer to the end of the term.
Throughout the course, you're bound to end up with questions about the material. You can always send me emails with these questions, or questions about how to use your calculator, Microsoft Excel, or Google Sheets, or anything else related to the course. I've also created a course Discord server where you can ask questions to other students in the class or to me. The link to this is available in the video description as well as on the on page.
With all of that out of the way, let's talk about what we're actually going to be learning about this course, and why that is statistics. We'll start with an example. Suppose you're going to be getting a new puppy. There are a lot of considerations that go into deciding on a puppy, but one of them is how big your new dog will be. One way you can determine that is to look at the size of all other dogs in the same breed. If you knew the size of all the dogs like your future puppy, you could find out the most common sizes, as well as the biggest size of dogs and the smallest size of dogs. This group of all of the dogs is called a population.
Now, in practice, we don't have access to all of the information in a population. So, we try to study what's called a representative sample of the population. In this case, this is a smaller group of dogs where the characteristics of the group are about the same as the full population. The idea is that learning properties of the sample will give us the information that we want about the full population. The process of trying to learn about the full population from a sample is called inferential statistics. And the goal of this course is to understand all of the different pieces involved in this process. This will involve learning how to collect representative samples, how to present and describe the information in a sample, how to estimate the properties of the population using properties of the sample, and how to make decisions about the population based off of the information that we find in these samples.
Each piece of this process involves a lot of uncertainty. And so, we'll need a good understanding of the mathematics behind uncertainty, which is probability, in order to accurately describe what's going on. As a result, we're going to be spending the first probably about 12 lectures going through probability theory before digging into statistics a little bit more deeply.
In the next class, we'll go through a bit of a mathematics review, reviewing some of the important things that we'll need to know for the course, including function notation and summation notation.