**Welcome to asynchronous remote Mathematical Statistics!**

As with all things in this era of teaching, our course will be somewhat experimental. While I have tested many of the specific elements we will be using in this course in other contexts, this particular format is a new one for me. I welcome comments and suggestions as we go. My primary goal throughout the semester will be to provide an effective and engaging environment for you to learn the course material. All other considerations will be secondary.

While the course is asynchronous, meaning there will not group lectures at a specific time, I will make an effort to schedule informal office hours at times which are convenient for as many students as possible, and will make myself available for scheduled appointments as well.

We will cover roughly the material in *John E. Freund’s Mathematical Statistics with Applications* by Miller and Miller. I’ll be using the 8th edition for my own reference. Having access to the material in the textbook will be important.

We will assume that the material in the first 7 chapters will be familiar from a previous course in probability, such as Rutgers MATH 477. Roughly the first two weeks of the course will provide a brief review of some aspects of this material, focusing primarily on chapters 3, 4 and 7.

To prepare for the course, it would be recommended that you review probability, paying special attention to the notions of expectation, mean, variance, covariance for random variables which are discrete as well as for continuous variables. Other important concepts include moment generating functions, the law of large numbers, and the central limit theorem.

The structure of this course is subject to some degree of change, as we are all adjusting to a new environment of university education. This said, we will start with the following plan:

Video material will be made available Monday and Thursday mornings, with short assignments due roughly 24 hours after the videos are posted. These will be primarily graded for completion, and you will have the opportunity here to give feedback on your understanding of the material, so that I know which things are well understood and which things are less clear to everyone. In addition, there will be a standard length weekly homework assignment given out on Tuesday and due Thursday. Finally, once a month we will have longer cumulative homework assignments.

The course grade will be based on these homework assignments as follows:

- semiweekly assignments: 40% total (drop lowest 4)
- weekly assignments: 30% total (drop lowest 2)
- monthly assignments: 30% total (drop lowest 1)

To be successful in the course will require:

- Keeping up with readings in the textbook,
- Watching the video lectures (twice per week)
- Keeping up with the written assignments,
- Asking questions via written assignments, email or during office hours whenever something is unclear.

In practical terms, if you want to do well in the course, it is absolutely essential that you keep up with the material in a timely way. Late homework will generally not be accepted.

On Wednesday, we will take some time for coffee hours/ office hours/ tea time. This will consist of an open Zoom meeting for roughly 2 hours where students can drop in and chat. While course questions will have precidence, everyone is welcome to come by and socialize as well.