Data Muse

Source(s): I used that statistics from a report by the National Center for Education Statistics (NCES), “The Condition of Education Employment. Outcomes of Bachelor's Degree Holder"  [1] , which used 2018 data from the Census Bureau. A table with similar relevant data can be seen  here  or can be queried from  https://data.census.gov/mdat . The exact numbers might differ based on query specifications, but the general trends are similar. Changes/Limitations to the Data: ·        Each of the major categories represents several sub-categories (e.g., “Biology” includes degrees such as “English,” “Biochemical Science,” “Botany,” “Ecology,” etc. ·        Only fields in which 1% or more of bachelor’s degree holders had earned degrees are displayed ·        For concision, I chose to exclude several categories (the NCES report had 34). Most of the majors I excluded were either ...

I collected this data by using each companies’ official android app. Using the home page of the app, I scrolled at a consistent moderate speed for the first 100 posts/elements and counted how many elements were advertisements or suggested content. Advertising behavior is a fickle thing and might change depending on how frequently you use the app, how and what advertisements you engage with, or even how quickly you scroll through the information. As such, your mileage may vary, but these were my personal results—take them for what they are worth.  I made the graphic in Excel and PowerPoint. I have provided more information about the collection for each app. Facebook: I use Facebook lite under 30m a day but nearly every day. A few times when scrolling (2-3/100 posts), Facebook “suggests” content or posts where I have not liked anything from the page nor had my friends engaged with it. I counted these suggestions as advertisements. Instagram: I use Instagram a few times a month and ...

Created February 6 th , 2020. US Presidential age at inauguration (and 2020 hopefuls) by year and party. Trendline showing mean and standard errors by party. I graphed this in R using ggplot2. Posted below is my annotated R code, data file, and sources. Looking at just the years since the GOP founding (1854), 51% of the variance in the "age at inauguration" is accounted for by party, election year, and the interaction between year and party ( F (3,27) = 9.37, p 2 = .51). R Code Formatted Data File Sources: Presidential Data Hopeful’s Age Data

Canadian Covid 19 Dashboard Social isolation can really change one's behavior. For me, it has meant spending a lot more time compiling and exploring different datasets in R. As I'm sure many others are, I have recently been playing with COVID-19 data. I was curious about how my home country of Canada has been handling COVID-19 so I created this dashboard to monitor the progress. Each graph hosted here is generated by my publicly available R code 1 and updates whenever I run the code (which tends to be daily). The data comes from official Canadian government reports 2 . If you have any questions, do not hesitate to ask. A few notes on the data... As one might expect, data during a pandemic isn't always accurate and up-to-date. There are several considerations when interpreting this data: New cases and deaths are reported on a 14-day rolling average. As day-to-day statistics can be volitile and influenced by systematic varaibles, I used a rolling ...