Finishing this summary assessment:
Choose two quantitative variables that you think may be associated. You can collect some data yourself or find lists on the Internet.
Before you conduct any analysis, What association ( Shape, Strength, Direction) do you expect to see between the two variables? Which variable is the explanatory variable and which variable is the response variable?
I’ll be looking to see if the following is present and correct.
- Table of Your two quantitative variables.
- Well labeled scatterplot (Axes with units)
- Correlation coefficient (r)
- Coefficient of Determination (r2 ) expressed either as a proportion/percentage and you explain what it means in the context of this situation.
- Least Square Regression Equation for predicting your Response Variable from your Explanatory Variable.
- An analysis of your results. You must relate your results back to part 1. This must include a discussion about r and r2
- You use your model to make a prediction for two values that are not part of the original data. One of these values must be an example of extrapolation. Identify this prediction.
- Discuss what the slope and y-intercept of your model means in the context of the situation.
- You suggest possible sources of confounding influences.
You can attach a publicly share link to a google doc/sheet.
Learning Target: I can find empirical and theoretical probabilities.
We’ll watch this <link>
We’ll collect some data and find probabilities
Once we are done with the data collection, Submit your results <link>