Algorithms are becoming more and more sophisticated, with that said it is plausible to arrive at the conclusion that algorithms pose threat to historical interpretions. However, I think as we move into the future this potential for error will become more and more minute as our data management and data storage will improve as well as the standards governing data. It will likely become harder to find gaps in digital history.

I feel that email has the ability to be impersonal, and the time spent reading an email cannot be equivocated to reading a letter. I think that we take more notice to a letter because someone took the time to write and mail this information.

I forget that data and visualization show up in entertainment as well. It is like this section says, you have to look outside of spreadsheets and text files to see that photos and status updates could also qualify. This just reminds me that data can be used in so many different ways and not just the more common ones you may think of off the top of your head. People like their entertainment so Facebook and OkCupid were most likely successful in using their data in that way.

This is very true that it is easy to spout averages and numbers while lumping another human being in as a statistic. I agree that the numbers do represent individuals so the data should be approached that way too. If we start talking about the people being directly affected by it instead of just going by numbers and data points more people would probably relate to it and learn more about it. This link https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1410028703 shows both the percentage and the actual number of people affected. This way we can see that the percentage does not seem all that big but the actual number of people affected is thousands.

I like the way that this was worded. I always thought of data as just numbers that you plug in and learn things from but that was all it was to me. The fact that it can be as complex or as simple as you want or as long or as short as you want means that each piece of data is unique to the person who created it. This has reminded me of the class and all of our final projects. We may be using some of the same software or tools to make our projects or we may even have a similar topic to someone else but each one is still going to turn out different. We will use the software and tools in our own way to represent the point we are making. This is something I have found throughout the whole course which is that even though each piece of digital humanities seems like there would only be one way to do it like data sets, there are actually so many interpretations and ways you can go with it.

Figure 1-6 and 1-7 look very different, and it could be hard to see that they are documenting the same set of data. This manipulation of data and how it is viewd can be used for very specific intents. If I wanted a client to see that my business has a consistent viewer rate, I would show them them figure 1-7's monthly chart, because of how smooth it looks. To me at first glance, it seems much more "consistent" than figure 1-6, with all of its spikes.

This is also an important part of marketing. While there is a specific "thing" or "data" that is being produced, the facts are not necessarily all that you're looking for. You want to look at how this connects to the readers or buyers, what it makes them feel and think. Ultimately, the goal is to make these people buy into the thing/idea etc. being sold, .

I think the whole idea of visualizations and statistics is to create something relateable. Without providing context there would be no way for the general public to interact with the data without intense reading and critical analysis. And, let's be honest, who really wants to do that much thinking about every little thing? Creating visualizations help us all to understand complex ideas easier.

It also helps us to visualize these complex data sets to see patterns and themes that could have otherwise been overlooked. Not only do these visualizations help the general public to understand, it also helps professionals in their field analyze data within different contexts to see all of the potential.

I believe this is very important. I think a lot of people tend to forget who they are presenting to, and lots of the valuable information goes to waste. In m Health Care Systems class we were always presented with lots of statistical data but nothing was every explain nor was the source the data was collected from presented so it seemed very misleading. Lots of numbers were thrown around without a true explanation given. After reading through this article, it seems more information was needed for both the students and the professor to understand the information provided.

This reminds me of Organic Chemistry labs. When data points don't make sense, something must have gone wrong in the experiment. It was vital to ensure that the source was found to determine if it would effect the results or if the experiment needed to be redone.

I wonder why bubbles were used instead of a geographical map displaying the percent? I know it mentions how it puts people to sleep, but wouldn't this be more confusing?

This seems extremely difficult to follow. I'm wondering how people who are colour blind might interpret this chart due to the similar colours used to display the stats.

Remember to see how many times that video has been uploaded. Also check for the date in the title could also instigate that it is a fake.