Amount of Soda Consumed and Individual's Weight
Participant	Number of 12 ounce sodas consumed per day	Weight
1	5	125
2	10	180
3	0	110
4	2	110
5	5	130
6	8	205
7	1	105
8	3	130
9	15	200

You now know the difference between correlation and causation. Although there are several different ways to make predictions, a regression analysis is one way to do so.The videoabove explains how to do simple correlation, regression, and scatterplot in Excel.

Remember, you can always visit your Lifeline for more help. For this assignment, imagine you are looking for a link between soda consumption and weight. Here is your data set:

https://www.youtube.com/watch?v=NGFmRt2V8vo

https://www.youtube.com/watch?v=g_PH5FKBJJY

ASSIGNMENT INSTRUCTIONS

Following the instructions in the video, enter your data set on an Excel worksheet. Be sure and use the labels provided in the data set. Then:

• Perform a correlation and regression on the data in Excel.
• Create scatterplot with a regression line for your data using Excel
• Discuss your findings as if you were explaining to an individual the impact of soda consumption on weight. Is there a significant relationship between soda consumption and weight? Explain how you know this. Using your regression, predict how a person's soda consumption will impact their weight (how much will drinking additional sodas increase an individual's weight based upon your findings for this specific data set).

You now know the difference between correlation and causation. Although there are several different ways to make predictions, a regression analysis is one way to do so. The video above explains how to do a simple correlation, regression, and scatterplot in Excel. Remember, you can always visit your Lifeline for more help. For this assignment, imagine you are looking for a link between soda consumption and weight. Here is your data set: Amount of Soda Consumed and Individual's Weight Number of 12 ounce sodas consumed per day