For the Normal Model Experiment:
In class, you were asked to do one of three things to collect 50 pieces of data (If you didn't do this in class, you will need to over the break).
1. Roll a pair dice and record the total on the dice each roll
2. Shuffle a deck of cards and start flipping over cards one at a time... counting until you reached an ace and record that number
3. In a bucket, shake up 10 pennies, then dump them out on the table and count how many are heads up and record that number
Using your 50 pieces of data, you were asked to create a Normal Model representation of the data, a Box Plot (showing outliers if any), and a Histogram.
For the write-up:
In class we have been discussing how to write good, meaningful sentences that compare values in the normal model and analyze the data as a whole. Step 1: You need to write 7 of these quality sentences looking at your normal model that represents the data you collected.
(These should NOT be the same sentence written seven times with different numbers inserted.)
Use the examples from class as a guide and don't be afraid to use actual data values, percentiles, and/or z-scores to discuss the data.
Use words like above, below, between to add variety to your sentences. Step 2: Fold a new paper long way down the center.
As you look over and edit your sentences, write the good ones down the left side of the paper.
(Make sure to leave a space between each sentence.)
This NORMAL MODEL that you have drawn may or may not represent the numbers you have actually collected. We have discussed many times before that the MEAN (the average) does not always give the best representation of the data we are looking at. The Box Plot and the Histogram you created represent the actual data you collected and show the distribution of that data. You are to determine if the NORMAL MODEL does the same in this situation or if it does not fit well.
Step 3: On the right side of the page, for each sentence you wrote, you need to prove or disprove that using your actual data and the other graphical representations. For example, if you told me on the left that the NORMAL MODEL indicates that 50% of the data should be above 7.6, but when you look at your box plot and find the median at 3.5 instead (since we know that the median is the literal middle of the data) then the box plot is telling us that values all the way down to 3.5 would be included in the top 50% of the data. And to verify this, you could count the data from your actual list that you recorded when doing the experiment... how many data values are above 7.6? how many are above 3.5? Also, remember that we are only looking at 50 data values, which is really not that many - so if you were to say that 50% of the data falls above 7.6 and when you counted your data from the list, you found that 23 values were truly above 7.6, then that is pretty much half and we could argue that the normal model is accurate representing the data for that statement.
In class, you were asked to do one of three things to collect 50 pieces of data (If you didn't do this in class, you will need to over the break).
1. Roll a pair dice and record the total on the dice each roll
2. Shuffle a deck of cards and start flipping over cards one at a time... counting until you reached an ace and record that number
3. In a bucket, shake up 10 pennies, then dump them out on the table and count how many are heads up and record that number
Using your 50 pieces of data, you were asked to create a Normal Model representation of the data, a Box Plot (showing outliers if any), and a Histogram.
For the write-up:
In class we have been discussing how to write good, meaningful sentences that compare values in the normal model and analyze the data as a whole.
Step 1: You need to write 7 of these quality sentences looking at your normal model that represents the data you collected.
(These should NOT be the same sentence written seven times with different numbers inserted.)
Use the examples from class as a guide and don't be afraid to use actual data values, percentiles, and/or z-scores to discuss the data.
Use words like above, below, between to add variety to your sentences.
Step 2: Fold a new paper long way down the center.
As you look over and edit your sentences, write the good ones down the left side of the paper.
(Make sure to leave a space between each sentence.)
This NORMAL MODEL that you have drawn may or may not represent the numbers you have actually collected. We have discussed many times before that the MEAN (the average) does not always give the best representation of the data we are looking at. The Box Plot and the Histogram you created represent the actual data you collected and show the distribution of that data. You are to determine if the NORMAL MODEL does the same in this situation or if it does not fit well.
Step 3: On the right side of the page, for each sentence you wrote, you need to prove or disprove that using your actual data and the other graphical representations. For example, if you told me on the left that the NORMAL MODEL indicates that 50% of the data should be above 7.6, but when you look at your box plot and find the median at 3.5 instead (since we know that the median is the literal middle of the data) then the box plot is telling us that values all the way down to 3.5 would be included in the top 50% of the data. And to verify this, you could count the data from your actual list that you recorded when doing the experiment... how many data values are above 7.6? how many are above 3.5? Also, remember that we are only looking at 50 data values, which is really not that many - so if you were to say that 50% of the data falls above 7.6 and when you counted your data from the list, you found that 23 values were truly above 7.6, then that is pretty much half and we could argue that the normal model is accurate representing the data for that statement.