# SOCR Events May2008 C5 S1

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 Revision as of 21:28, 8 February 2008 (view source)IvoDinov (Talk | contribs) (→Estimate the equation of a line of best fit to make and test conjectures)← Older edit Current revision as of 21:28, 8 February 2008 (view source)IvoDinov (Talk | contribs) Line 15: Line 15: ===[[SOCR_EduMaterials_Activities_BivariateNormalExperiment | Estimate the equation of a line of best fit to make and test conjectures]]=== ===[[SOCR_EduMaterials_Activities_BivariateNormalExperiment | Estimate the equation of a line of best fit to make and test conjectures]]=== - ===Interpret the slope and y-intercept of a line through data === + ===[[SOCR_EduMaterials_Activities_BivariateNormalExperiment | Interpret the slope and y-intercept of a line through data]]=== - ===Predict y-values for given x-values when appropriate using a line fitted to bivariate numerical data=== + ===[[SOCR_EduMaterials_Activities_BivariateNormalExperiment | Predict y-values for given x-values when appropriate using a line fitted to bivariate numerical data]]=== ==References== ==References==

## SOCR May 2008 Event - Summarize, display, and analyze bivariate data

### Collect, record, organize, and display a set of data with at least two variables

Use the Hot dog Sodium Calorie Dataset and explore various bivariate activities.

### Characterize the relationship between two linear related variables as having positive, negative, or approximately zero correlation

Try scatter plotting the Weight or the Height (Y-axis) agains the index of the observation for the first 100 subjects in the Human Weight/Height Dataset. Of course, there should be no correlation between the index of the subject and his/her height or weight, as subjects are randomly chosen! On the contrary plotting Weight vs. height will demonstrate a clear positive correlation (i.e., higher weight implier taller individual).

## References

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