Module Two

Categorical Data Sort and Analysis

When I saw the list of names, I thought of the variety that was given. Some of the names I hadn't heard of before so it was interesting to look them up and see who are they and what I thought would be a conversation that I could have with them. I ended up doing about 5 or 6 different sorting's and one of them I chose to do was names I knew versus having to look them up. I knew of 17 of the names (counting Jesus Christ twice) and 6 of the names I was not familiar with. 

The sorting that I want to share with you is: 

Who is this person?

Activist	Actress	Artist	Political	Musician	Novelist	Computer Programmer	Religious	Royalty
Rosa Parks	Lauren Graham	Antoni Gaudi	John F. Kennedy	Drake	Jane Austen	Bill Gates	Jesus Christ	Queen Victoria
Haregewoin Teferra	Oprah Winfrey		Barack Obama	Paulo Coelho	Malala Yousafzai	Mark Zuckerberg	Jesus Christ	Queen Elizabeth I
Malala Yousafzai			Michelle Obama		Paulo Coelho	Aaron Swartz		King Leonidas
			Maxine Waters		Oprah Winfrey
			Nelson Mandela		Michelle Obama
					Mark Twain

Sorry the chart wouldn't line up any better.

If we look at the way I ultimately decided to sort the names, some of us thought about influential people of the past and present in relation to political people. Though one could classify musicians as a type of artist, I chose to keep Gaudi separate from the others. While I didn't personally think of Jesus Christ when I first read the question, I found it interesting that only two classmates thought of Him. Another thing I noticed was that a few of the names could go into different categories, and I wasn't really sure if that was okay or if it "messes" this data graph up. What do you think Aubrey?

To further this data, one could ask a more concise question such as, What one political person would you have a conversation with, dead or alive? Or What one activist? 

I did have some names that I wasn't sure how to put on my list, what I ended up doing was doing a little more research on the person to see how I could maybe rename or classify a group I already had listed. I had difficulty with where to put Queen Elizabeth, Queen Victoria, and King Leonidas, but I came with with Royalty. I originally had Mark Zuckerberg and Bill Gates as Social Media, but realized that that was not really a good fit, when I thought about what they did in creating a program I was able to also place Aaron Swartz in the group.

Students in a classroom would be able to share similar responses, I think that this activity could really show the realm of understanding that the student may have in terms of people that influence them enough to want to have a conversation. 

Aubrey, do you think I could have narrowed down my categories to have a few less columns? Do think it was okay to put different people into more than one grouping? 

Article- Statistics in the Elementary Grades

I don't remember much from my elementary years, but after reading the article I feel like we did the shoe thing at least once growing up. As I was reading the article I was surprised at the many different ways one could interpret the questions and the results. For the shoe data, it suggests "pushing the students' thinking with extension questions" for example is type of shoe related to age? I don't know if I would have thought of that question as a child, but the question is valid and it could change the data collection based on the grade level. 

For the soccer goal problem, analyzing the data was different. I don't recall hearing the fair, or equal share that is talked about in the article. Aubrey, have you heard of this before? I have not had any data experiences in my field experience classrooms that I have been in, and I would really like to see this thinking in action, and whether or not the teacher can actually engage the students in the understanding of "difference in distributions of data." Aubrey have you had the chance to see data collection in any field experience classes? 

How Many Pockets? Video

As I was watching this video I noticed that first the teacher just asked a simple question, "How many pockets do you have?" At first she didn't explain, she gave them time to count what they had on and what they considered a pocket. After a few seconds the teacher again asked the students a question, but this time it was for more of a clarification of what was considered a pocket. I noticed that once she made this comment that several of the students began to double check and recount the pockets that they had. As the students started to review the data that they had collected they were able to make connections between the number of students that had a select number of pockets, however, some students struggled with the wording concepts and needed help from classmates. I felt that the teacher was active enough in the conversation to allow the students to build upon what they had learned, she was also able to help the students create a higher level of thinking and exploring. The one thing I wasn't happy with is that the teacher mentions predictions, and we did not hear what the predictions were. 

But the students are working on learning about numerical data collection and how to process the information they gathered. Aubrey, I think the students had some confusion on counting the number of pockets they had and if they had reported it to the teacher, what do you think? 

When reviewing the data collected, I thought the teacher did well on keeping the students on the same idea to help explain the results that they saw. The teacher also made sure that the students used the proper wording of "some" instead of "most". 

Exploring Questions

When dealing with a statistical process we must first formulate a question. The question should be answered with data that can be used for an array of other information once gathered. The next step is to collect the data, this can be done in a variety of different ways depending on the question asked. The third step is to analyze the data, this is the process that separates the information they gathered into the categories that they belong with. The final step is interpreting the results, here you would summarize the data and consider other questions that could be answered based on the results.  For example, we could ask inside a classroom: What is your favorite food to eat for lunch?

Observing a group of people was difficult, but I did while waiting in line at the grocery store. So many different ways to categorize them came to mind. Did they have a purse? How did they pay for their purchase? How many items did they have in their cart? And since it is a grocery store, was it an individual shopping or a entire family? 

Any of these ways can have interesting results, looking at how they paid for the groceries can lead to more informative data collection. The grocery store could use that data to decide whether or not more self checkout machines would be useful or if having a cash only line could benefit customers. 

I never thought of all the different ways in which one could categorize a single experience but the ways are unlimited.