Reflecting on My Learning: Introduction to Statistics

Image via lendingmemo [CC BY 2.0]

This semester I'm taking a couple of courses for my grad work, as usual lately. To be honest, I was pretty nervous for this semester, because I am taking my first ever statistics course.

Yep, that's right. I made it through high school, my undergraduate work, and even my M.Ed program without a required statistics course. (To be fair, in my M.Ed, we did take a "Research in Education" course that included just enough statistics to help us become good consumers of quantitative data, but we didn't do much with creating quantitative analyses.) I'm enough of a "math guy" to feel confident in my ability to do algebra, and I taught math, and even math methods for elementary teachers as an adjunct instructor. I know the measures of central tendency, I know how to create a bar graph and a line graph and a scatterplot, I understand P-values. But there is a lot of arcane terminology in the first few chapters I've read for the course... Skewness. Kurtosis. Nominal vs. Ordinal vs. Interval Variables.

While working on my homework early in the course, I tweeted:

Doing my stats homework makes me feel both smart and dumb at the same time. #gradschoolproblems
— Dave Mulder (@d_mulder) September 4, 2014

It's true. I am proud of myself for the work I've done so far in this program. I know things I did not know and have skills I did not have this time last year. I know I'm going to understand statistics too.

But there are moments when I doubt my abilities. I have to read and reread things. I am learning how to use a piece of software I have never used before. I am mastering terminology and techniques I need to know, but it hasn't come easy. I'm working hard, and connecting with my cohort, and discussing the ideas from the readings, and doing my homework earlier rather than later.

This course is going to challenge me, but I know I can do it. It's been a good first few weeks.