Thread: "Make a single display of all the weights" - what does this mean?

1. "Make a single display of all the weights" - what does this mean?

I am having difficulty with a homework question relating to a dataset with 92 cases. I have not been able to paste the table here but have included the variables (see below):

Pulse Before Pulse After Ran? Smokes? Gender Height Weight Activity Level

This data came from an in-class activity in a college introductory statistics class. Some general data was collected for each student, and then each student was asked to flip a coin. Those whose coin came up heads were asked to run in place for a minute or so. All students measured their own pulse rate both before and after the running activity took place. Note that the two measurements were made on those who ran and on those who did not.

In addition to the pulse rate before and after the running took place, the data recorded whether each student ran or not, whether they smoked, their sex, height (in inches), weight (in pounds) and activity level. This last is coded

1. low
2. moderate
3. high

The question I am having difficulty understanding is:
Make a single display of all the weights. Choose a display that shows the shape of this distribution. Try more than one scale. Then comment on the shape you see and anything else you find. (You do not need to submit the actual graph.)
If anyone could explain what is required here in simple language, this would be most appreciated. I am having difficulty understanding:

(1) what is supposed to be included in the graph (e.g. which variables)

(2) what kind of graph is necessary.

Bear in mind that the graph would be based on 92 cases.

2. I think this is a really easy question which just requires you to display the weights. Forget everything else. Group your 92 pieces of data into a frequency table (eg. 70-75kg, 76-80 kg, etc). Choose appropriate band widths to suit the data you have. A histogram would be appropriate (or a stem and leaf plot).

3. Originally Posted by Debsta
I think this is a really easy question which just requires you to display the weights. Forget everything else. Group your 92 pieces of data into a frequency table (eg. 70-75kg, 76-80 kg, etc). Choose appropriate band widths to suit the data you have. A histogram would be appropriate (or a stem and leaf plot).
Thanks Debsta

I have not come across the word "weights" in statistics before. If you could explain what "weights" means that would be much appreciated. Also, what variables should be included in the frequency table? e.g. pulse before, pulse after, students who ran, students who did not run, gender, height, activity level?

4. It's not a statistical term, just one of the variables you have gathered data on ie "weights" as in "how many pounds do you weigh?" Forget all the other variables such as pulse, height, gender etc. The question is asking you to make a single display of all the weights. So the only variable you need consider here is "weight". I mentioned kg (I'm an Aussie) but you will do it in pounds. What is the least weight you have recorded and the greatest weight. Say 50 pounds and 150 pounds. Then split your data into groups (about 8 to 12 groups would be good) eg 50-59 lbs, 60-69 lbs etc and count up the frequency.

5. "try more than one scale" simply means to produce a few different graphs using different band widths (ie start with 50-59, 60-69 etc, then try 50-54, 55-59, 60-64 etc). These numbers mightn't be the best for your data. use your lowest and highest value as a guide.

6. Originally Posted by Debsta
It's not a statistical term, just one of the variables you have gathered data on ie "weights" as in "how many pounds do you weigh?" Forget all the other variables such as pulse, height, gender etc. The question is asking you to make a single display of all the weights. So the only variable you need consider here is "weight". I mentioned kg (I'm an Aussie) but you will do it in pounds. What is the least weight you have recorded and the greatest weight. Say 50 pounds and 150 pounds. Then split your data into groups (about 8 to 12 groups would be good) eg 50-59 lbs, 60-69 lbs etc and count up the frequency.
Thanks - very helpful. For some reason I overlooked the weights variable.