web design

I confess that graphic design is not my strong suit, by any stretch of the imagination. I’m much more useful behind the scenes. But web accessibility is so important to me that I needed to learn more about the front end. I’m in the middle of this Web Design for Everybody specialization. It’s been fantastic, and it’s another University of Michigan series on Coursera– I’m so impressed with the University of Michigan! So far, I have completed the HTML course (a sample of some HTML scribbles), and nearly-completed the CSS course (a sample of some CSS scribbles), and I am halfway through the JavaScript course. I have a much healthier appreciation for how much work goes into a fully functional website– and I’ve recommitted myself to making my code the most accessible as possible. Whether it’s a blog post or a full-blown app. The internet is awesome. It should be accessible to everyone who wants to access it, with no exceptions.

I am excited to say I’ll be helping out with the Aardwolf project, a decentralized and open-source alternative to Facebook that was inspired by Mastodon, an open-source microblogging platform. I drafted Aardwolf’s Code of Conduct, and will be helping with accessibility features, as well.

winding down and ramping up

I’ve finished the Web Applications for Everyone Coursera specialization! (proof!) I have really come to like Coursera’s format for learning, but I think what really made me love it (first with Python for Everybody, and now with WA4E) was Dr. Chuck’s teaching style and course materials. It was nice to feel like I was “back in school” again, but it was even better to be able to work at my own pace. I’ve surprised myself by how quickly I went through most of the material, and really grateful to have been able to spend extra time on parts I found complex or parts I really wanted to take the time to explore and enjoy. Coursera is a pass/fail program, but you do get a numerical grade for your own records: I finished WA4E with a score of 99.7 percent.

WA4E and Py4E are all open education resources and can be used and reproduced without permission. I highly recommend them. (Start with Python if you’re new, like me! Python was a great first language.)

I have been thinking about where I’d like to go next. The web applications courses were about back-end app development, and there’s a complementary specialization for web design, which is more front-end and making things pretty– and accessible. Accessibility is near and dear to me, and will forever influence my development and engineering. That may be my next step.

I think I’ll be taking a little more time to wind down and polish up some more projects to show you here (or github), and gearing up to really ramp up my involvement in some interesting open source projects… with some serious job hunting, too. But in the meantime, I think I’ll be checking out Advent of Code.


PHP, SQL, and security

I have been working my way though Dr. Chuck Severance’s Web Applications for Everybody, via Coursera. It’s a four-course specialization that uses PHP and SQL, and I’m enjoying it very much. SQL is fun and interesting (and this will help when I go back to the Python Data Specialization), and PHP is one of those things I recognized in the URLs of browsers, and random error messages I’ve seen over the years, but I had no idea what it was. Now I can make some short programs to do some simple database work focusing on CRUD: Create, read, update, and delete.

I am also all-but-finished with a Cybersecurity for Business specialization. These courses rely on peers to review certain assignments, and the courses don’t seem very active with students– I’ve had trouble getting responses to questions, and right now I’m just waiting on another fellow student to submit an assignment so I can complete my last peer review and finish the specialization. It was pretty interesting– especially as a small business owner without a lot of experience but having read a lot of scary stories about hacks and leaks.

I’m working on re-working some of my PHP and SQL projects so that they don’t violate Coursera’s honor code when I include them in my portfolio. πŸ™‚

prioritizing accessibility

I’m going to be attending a teach-out about the internet and society. The instructors requested questions and comments before the teach-out begins at the end of the month, but the phone number is a google voice number with a limited voicemail length and I didn’t realize they didn’t want a WHOLE me-length comment. πŸ™‚ So I’ll just post it all here:

I’d like to discuss accessibility and the internet.

I first discovered the internet in 1995. I grew up in rural New England, in a very isolated and sheltered area. My father was from Brooklyn, so I knew that the world was much bigger than the tiny little farm town where we lived, even if I hadn’t actually visited these places myself.

When I got online for the first time, it changed my whole world.

Suddenly I could communicate and collaborate with people from places I’d only dreamed of. Suddenly my world became much larger than the tiny little town with its one general store and no traffic lights.

My new internet friends were mostly tech workers and researchers, but we were a diverse group. I had friends who spoke little English. I had friends not just outside New England, but in other countries on other continents.

This was mind blowing, after graduating from a class with 150 students. Walls came down. Borders and geographic location became nearly irrelevant.

It made the world bigger and smaller all at the same time.

I had friends who were blind, I had friends who were physically disabled and could only type using one button on a mouse. The internet, and the computers we used to access the internet, were improving, and it felt like this was becoming the great equalizer. Differences and disabilities became less of a barrier on the internet.

People with disabilities have historically been isolated in institutions or other oppressive situations where we get little access to the outside world, and now suddenly we can access the world from our bed.

But now, over 20 years later, I feel like we have regressed. The internet has simultaneously become more integral AND more exclusive than ever.

We exclude Deaf and hard of hearing people by refusing to caption videos or post transcripts.

We exclude people with vision impairments when we use images without descriptions, excessive graphics and popups, invasive advertisements, auto-playing videos with sound, low contrast styling, and just plain old bad design.

We exclude people with seizure disorders by using flashing animations without warning.

We exclude people with PTSD by posting unsolicited violence without content warnings.

Accessibility isn’t just about helping those of us with disabilities. It’s about helping those of us with limited data plans, without high speed internet, with older slower devices, with lower incomes, with language barriers.

Accessibility doesn’t just help those of us who need these accommodations right now. Prioritizing accessibility means that people who become disabled tomorrow will still have access. Prioritizing accessibility means that as today’s developers age, they’ll still be able to use their own products when they’re 100 years old and relying on their reading glasses and hearing aids.

I want accessibility to be a higher priority online. I’m often met with significant resistance when I request accessibility improvements, sometimes because the perceived demand isn’t high enough to justify the time and money required to improve it, and sometimes because the content producer simply doesn’t think it’s important enough to prioritize.

Let’s prioritize accessibility.

And let’s talk about how we can make that happen.

internet history, and moving forward

I completed Dr. Chuck Severence’s Internet History, Technology, and Security course on Coursera (verify here), and it was an outstanding overview of how we arrived where we’re at today, and helped me wrap my head around the backbone of our wired world.

My only real experience with layered architecture was a very abstract understanding of the OSI model, and this course focused on the TCP/IP. I’ve realized that network architecture is really interesting, and I’d like to learn more.

Learning more Python and becoming more comfortable with online learning environments has helped make learning more python and becoming more comfortable with online learning environments easier and more fun. There’s been a bit of a learning curve not only because this is a new format for me, but there are accessibility concerns I needed to navigate: Utilizing transcripts, bad connections, resource-intensive applications, avoiding flashing or glitchy videos, avoiding exacerbating chronic pain.

This has all renewed my interest in Free Code Camp, which wasn’t a good fit when I first tried a few months ago, but it turns out that it’s actually really awesome. My tribute page to Victor of Aveyron was a Free Code Camp assignment, and an opportunity to learn more about disability history.

changing specializations

Hello, friends and classmates! If you’ve followed me here from Coursera’s Data Management and Visualization specialization (the one through Wesleyan), I wanted to let you know that I completed the first class and decided not to pursue the rest of the specialization. I was a little disappointed with how inactive the forums are– this topic is so new to me that I admit I’m relying on my classmates (and StackOverflow) a LOT. Also I’m really loving Python– I want to run with that, and this specialization was more about the process than about the programming. If you’ve already got some programming knowledge and want to learn about stats, I do recommend it. The instructors were incredibly knowledgeable.

I switched over to the specialization in Applied Data Science with Python, and this has been a good fit so far. I’m not sure how much I will be blogging about these specific classes (not only is maintaining an assignment blog not part of the course, but due to the nature of the material, it’s against the honor code to post specific assignments).

In case I switch over to more general blogging and less educational stuff, thank you to my classmates for following along. Best of luck with your studies, and please stay in touch! And look me up if you end up over in the Python data science classes. πŸ™‚

Data Analysis Tools, week 1: hypothesis testing and ANOVA

Welcome to the first week of the second course in Coursera’s Data Management and Visualization specialization. In order to utilize ANOVA and post hoc testing, I needed to examine a different explanatory variable than in the previous course. This analysis will examine whether or not a person’s gender and race is associated with their support of the death penalty, as punishment for murder. I will still be using the Outlook on Life (OOL) surveys, made available by ICPSR for Coursera students.

Hypotheses to be tested:

Null hypothesis: the death penalty is supported equally among all gender-racial groups.
Alternate hypothesis: support for the death penalty varies among gender-racial groups.

The categorical response variable was a combination of two groups: those who know someone who has been arrested for a crime, and those who have a friend or relative who has been convicted of a crime. This variable had two categories: yes and no.

The new categorical explanatory variable contains four (4) categories: white men, white women, men of color, and women of color. The gender choices were extremely limited in the dataset: male, female, and no response. Because it was not possible to know if a “no response” was a refusal to answer or identifying as a transgender or nonbinary person, these individuals were omitted from the sample. For more comprehensive data analysis, the survey should have used “masculine” and “feminine” instead of “male” and “female,” and included options for transgender, nonbinary, and possibly other gender identities.

An analysis of variance (ANOVA) revealed that among this sample, the gender and race of an individual (collapsed into 4 categories, as the categorical explanatory variable) is significantly associated with a preference for the death penalty. Utilizing an ordinary least squares (OLS) approach, the following results were obtained: F-statistic = 32.57, p = 2.10e-20. Tukey’s Honestly Significant Difference post hoc test was conducted to determine which groups were significantly different from each other. There was no significant difference in the results between white men and white women, therefore we accept the null hypothesis; however, there were significant differences between white women and men of color, white men and men of color, men of color and women of color, white women and women of color, and white men and women of color, and we accept the alternate hypothesis for these groups.

The punishment preferences among the groups are as follows: 66.7% of white men favor the death penalty, 58.8% of white women favor the death penalty, 55.6% of men of color favor imprisonment, and 64.7% of women of color favor imprisonment.

I was unable to calculate standard deviation for these results. I do not think this is possible, because the explanatory variable has 4 categories, and the response variable has 2 categories: neither are quantitative. After spending many hours (at least 16!) trying to find and code quantitative variables relevant to my original thesis, I was unsuccessful. I understand the code involved in calculating means and standard deviations, but I was unable to show that in this assignment. If any of my classmates have some input or resources, I’d welcome the assistance. I would very much like to calculate the deviation between each of the four gender-ethnic groups.

Click to read the rest….

week 4: creating graphs

This week’s goal was to create univariate and bivariate graphs for the data that was managed in week 3.

Research question, to recap: Do people who know someone who has been accused or convicted of a crime favor the death penalty over life in prison as a punishment for murder, and does this preference differ from people who have never known anyone accused or convicted of a crime?


bar graph
Out of 1490 responses, 51.28% favored imprisonment over the death penalty, and 48.72% favored the death penalty as punishment for murder.

Click to read the rest….

week 3: managing data

The goal for this week was to identify and perform any data management that will help to answer the question clarified in week 2:

Do people who know someone who has been accused or convicted of a crime favor the death penalty over life in prison as a punishment for murder, and does this preference differ from people who have never known anyone accused or convicted of a crime?

I did not realize that I was jumping ahead when performing some data management in the previous assignment. In order to answer this question, I needed to combine those who answered β€œyes” to one or both of the following questions: β€œhas anyone in your household ever been arrested for a crime?” and β€œdo you have any friends or relatives having a criminal conviction?” into one group, and combine those who answered β€œno” to both of these questions into a second group.

By the nature of the convert_numeric() function, individuals with missing variables were excluded. Individuals who refused to answer the questions are included in the analysis, because their responses were coded as (-1). However, it was impossible to determine why variables are missing from the dataset at this level of investigation. Because these answers cannot be inferred, the individuals were omitted from the analysis.

Click to read the rest….