Chapter 12 Project
Linear Correlation and Regression Project
Collect data for two variables. Collect at least 15 pairs of such data. Be sure the data follows the necessary requirements presented in chapter 12.
State your hypothesis/claim in words so I know what two variables, x and y, you are analyzing.
Clearly organize your data in a table and graph it as a scatter plot on a set of axes.
Find the linear correlation coefficient r and state what its value suggests about the relationship between x and y.
Test to see if there is a linear correlation between the variables x and y by finding the P-value. Include the hypotheses, how the p-value determined the conclusion of the hypothesis test and a written interpretation of that conclusion in the context of the claim (hypotheses). Use a 0.05 significance level.
Find the regression equation and accurately draw and label it on your scatter plot.
Use the regression equation to make a prediction about the population your data came from. Do this even if your hypothesis test says no correlation exists. For example, if a father’s height is 83” what is the predicted height of his son?
Variable Examples (but please feel free to get creative – use our class data, or try using data analytics from your phone or smartwatch or social media accounts)
The heights of a father and son
The number of square feet in a house and the number of people living in that house
The number of hours people spend exercising each week and their resting heart rate
Number of miles on an odometer and the mean number of hours driven per day
Number of hours on your phone each day and the number of apps on your phone
NFL team wins this season and total number of points scored this season
People’s typing speed and texting speed
Student’s reaction time and typing speed
If you don’t want to use our class data, you can collect your own, just be sure to collect at least 15 pairs. Here are a few links to some other data sets that would work if you are interested in these topics:
Global Average Temperatures AnomaliesLinks to an external site.
Arctic Ice DataLinks to an external site.
World Grain Consumption DataLinks to an external site.
Hourly Wage by Race and GenderLinks to an external site.
Upload your completed assignment as a single pdf using the “submit” link below.
There is no sample assignment for this project. At this point in the semester you are well skilled at producing a complete hypothesis test and all its necessary requirements. Please only submit your neatest and best work. Sloppy and illegible work will not be graded. Please proofread your assignment for errors before you submit it. Check out the attached rubric for more grading specifications.
Chapter 12 Paper Assignment
Chapter 12 Paper Assignment
Criteria Ratings Pts
This criterion is linked to a Learning OutcomeClaim
Present your claim in words of linear correlation for the defined population and paired quantitative data.
2 to >0.0 pts
Full Marks
0 pts
No Marks
2 pts
This criterion is linked to a Learning OutcomeData
Organized data (at least 15 pairs) in a table and graphed in a scatter plot
2 to >0.0 pts
Full Marks
0 pts
No Marks
2 pts
This criterion is linked to a Learning OutcomeCorrelation Coefficient r
State its value and what it suggests about the relationship between x and y
3 to >0.0 pts
Full Marks
0 pts
No Marks
3 pts
This criterion is linked to a Learning OutcomeHypothesis Test
Test to see if there is a linear correlation between the variables x and y by finding the P-value. Include hypothesis written symbolically and in words. Indicate how the p-value determined the conclusion of the hypothesis test and a written interpretation of that conclusion in the context of the claim (hypotheses). Use a 0.05 significance level. Include how the results of the hypothesis affect the use of the regression equation.
3 to >0.0 pts
Full Marks
0 pts
No Marks
3 pts
This criterion is linked to a Learning OutcomeRegression Equation
Find the regression equation and accurately draw and label it on your scatter plot.
2 to >0.0 pts
Full Marks
0 pts
No Marks
2 pts
This criterion is linked to a Learning OutcomePrediction
Use the regression equation to make a prediction about the population your data came from. Do this even if your hypothesis test says no correlation exists.
3 to >0.0 pts
Full Marks
0 pts
No Marks
3 pts
This criterion is linked to a Learning OutcomePresenation
Careful and thoughtful attention was given to the presentation of your project
4 to >2.0 pts
Full Marks
The project is neat and free or errors such as typos, scratch marks or egregious grammatical errors. The project is coherent and simple to follow your thought process. Correct notation and imagery is used. If the assignment is hand written, it should be legible and written on clean paper and photographed or scanned legibly.
2 to >0.0 pts
Partial Credit
The project is fairly neat and free of major errors. Typos, scratch marks and grammatical errors are few. The project is mostly coherent and simple to follow your thought process. Correct notation and imagery is used. If the assignment is hand written, it is mostly legible and is scanned or photographed so it is legible.
0 pts
No Marks
4 pts
Total Points: 19
Chapter 12 Project Linear Correlation and Regression Project Collect data for t
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