1. A causal, complementary, parallel, or reciprocal relationship, especially a structural, functional, or qualitative correspondence between two comparable entities: a correlation between drug abuse and crime.

2. Statistics. The simultaneous change in value of two numerically valued variables: the positive correlation between cigarette smoking and the incidence of lung cancer; the negative correlation between age and normal vision.

So, a positive correlation between two things means that if you see more of the first thing, you will likely see more of the second thing. A negative correlation means that if you see more of the first thing, you will likely see less of the second. A zero correlation means that seeing more of the first thing has no effect on whether or not you see more or less of the second thing.

Correlations are measured by computing something called the correlation coefficient, usually abbreviated as r. The American Heritage Dictionary defines correlation coefficient as:

A measure of the interdependence of two variables that ranges in value from -1 to +1, indicating perfect negative correlation at -1, absence of correlation at zero, and perfect positive correlation at +1.

Gathering the Data

In this experiment, you will look for correlations between human body height and other human features. Chose at least 10 of your friends and family members to be subjects (the more, the better). Include yourself in the list of subjects. For each subject, record his or her age and gender. Then:

1. Measure his or her height, in inches.
2. Measure his or her wingspan, that is, the distance between he farthest fingertips on outstretched arms.
3. Measure the distance around his or her head at the widest point.
4. Measure the size of his or her hand, from the tip of the outstretched thumb to the tip of the outstretched pinkie.
5. Record all of these in the columns of a spreadsheet. Do not put the names of the units in the spreadsheet with the data, just enter the numbers.

When you have collected all of the data:

1. Copy and paste the spreadsheet columns into CricketGraph. Only copy and paste numbers, not any text column headings.
2. Do separate scatterplots of wingspan vs. height, head size vs. height, and hand size vs. height. To make a scatterplot, select Graph then New Graph then Scatter. For each scatterplot, place height on the X axis, and the other variable on the Y axis.
3. For each scatterplot, have CricketGraph compute r, the correlation coefficient. Do this by selecting Options and Curve Fit. Select a Method of Linear and a Coefficient Display of r, as shown below:

The closer r is to 1.0, the more correlation there is between the two variables.

Writing the Lab Report

On March 1, turn in a lab report on this experiment. This is to be done on one of the word processors. It needs to include:

1. A statement of what this experiment was trying to achieve.
2. The data tables from your spreadsheet.
3. The scatterplots from CricketGraph.
4. What, if anything, you were able to conclude about body measurement correlations from the results.

Data Collection on the Internet

As part of this experiment, we are also going to collect everyone’s data into one big plot.

To enter all of your data, run this page once per subject.