**Lost Teeth Video: **

1^{st} Video Segment- I believe that the teacher asked the students to think about the differences in the rage of each grade to get the students to realize the different information that will be projected on their data. I think she was doing this so that students can see that even if the range is high does not necessarily mean that grade has lost more teeth. I believe that the students thinking was very advanced when they were trying to hypothesize what the range would be. They were recalling the data they had collected and using life experiences to support their answers. Also, the students were remembering changes they had to make to their data and how that would affect the range. For example, in one of the classes the highest number of teeth lost was 12; however, a student that who had lost 12 teeth had lost another tooth that night. They had to move her to 13 because of this, which will affect the range.

2^{nd} Video Segment- I think the students noticed important features in the data. At the very beginning of this segment, the two girls presenting their data comment on how they thought it was unusual that one first grader had not lost any teeth, but that we was younger than the other first grade students. I think this was very important because it almost appears to be an error in their work; however, it shows that they were aware of this and researched this to make sure it was correct. Also, the students took time to see if the range matched the predictions they had made before. The majority of the students were surprised that the range was so high when they had predicted it would be lower. The students also took time to compare were their class had lost the majority of teeth versus the majority of teeth lost in the first grade class.

Final Video Segment- The students did a very good job of presenting the information from the kindergarten class. They stated the range was 0-6 and how it was surprising that one student had lost six teeth since the majority of students in that class lost 0 teeth. Both students did a great job of noticing important features in the data and comparing the data to their own class.

I think that the teachers asks the students to think about differences in the range at each grade level so students can see that if one grade level has a higher range, that doesn’t necessarily mean that they have lost the most amount of teeth. I think by students looking for this they were able to physically see that the range just had to do with the lowest number of teeth lost and the highest number of teeth lost. The children impressed me when they stated their reasons they believed the range would be different. They began recalling information and changes they had collected in their data to create a hypothesis. Also, I believe that the children did notice important features of the data. They could name the total teeth lost, the highest amount and lowest amount of teeth lost, the range, and much more data. Even on the graph representing the 3^{rd} grade class they had a category for students who could not remember how many teeth they had lost. I did not catch any features they did not notice.

**Describing Distributions Module from Annenberg:**

I was unsure of problem A6 part a. I know that the mean is approximately 62.35, but I don’t understand how it compares to the correct response of 60 seconds? I’m honestly just really unsure what this is supposed to show us about our data? Any help on this would be appreciated! J

I also was a little unsure of problem C5. I understand cumulative frequencies, but was a little thrown off by what the relative cumulative frequency was. The instructions said that to find the relative cumulative frequencies you would divide the cumulative frequency by the total number of data values. So since there was 52 estimates for the example, would you just find the cumulative frequency then divide it by 52? I think I’m making this a little more complicated than it should be, I just want to make sure I am not doing everything completely wrong!

I did really enjoy going over the stem and leaf plots and histograms. It has been a really long time since I have used a stem and leaf plot and I don’t think I’ve ever used a histogram graph before. Most everything was explained really easy and I thought it was really neat to see how the histogram graph works.

**Stem-and-Leaf Plots Article: **

I believe the most interesting thing I learned from this article is that elementary aged students are not too young to start using stem-and-leaf plots. I was amazed that the students picked up on it so easily. I remember having trouble with these for some reason in high school. I would just look at all the numbers and become confused. For some reason it just never registered to me the number on the left represented the tens place. The examples from Annenberg and this article have made it so easy to understand. I would love to use a steam-and-leaf plot in my classroom for the same example as in the article. I think using the parents ages was a great example and the children were really interested because the information was related to them. I believe that another good example would be when using a larger amount of data.

**Blog Questions:**

1. What kinds of graphs can be used for data that can be put into categories?

-There are many different graphs that can be used to place data into categories. One of the easiest example that we have been working with is the line plot graph. Below is an example of a line plot graph. We can place X’s over each category to represent how many is in that category.

Another example would be a pictograph. It has the same concept of a line plot graph. Below is an example.

Probably one of the most common graphs we use to place information into categories is a bar graph.

This bar graph is a great example that shows how to place 3^{rd} and 4^{th} graders favorite sports into categories. It also is a great example of how you can compare the two grades side by side to see a visual difference.

2. What is the difference between a bar graph and a histogram?

-A bar graph gives a single value for one category. It gives a specific answer.

In the bar graph above, we can easily see that the number of black cars that drove by was 10.

-A histogram does not give a specific numerical answer. Take a look at the example below.

We can see that there were 30 estimates made between 30 and 40, but we do not know a specific amount to make a definite answer.