


Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Community
Ask the community for help and clear up your study doubts
Discover the best universities in your country according to Docsity users
Free resources
Download our free guides on studying techniques, anxiety management strategies, and thesis advice from Docsity tutors
A project for math 130 students to analyze the relationship between the number of automobiles in the us and time using linear regression. Students are asked to create graphs, calculate slopes, and make predictions based on the data provided. The goal is to determine if a linear model is an appropriate fit for the data and to compare the results with excel's trendline.
Typology: Study Guides, Projects, Research
1 / 4
This page cannot be seen from the preview
Don't miss anything!
Background: Many scientists are interested in the subject of global warming. The basic issue concerns whether human activities are influencing the climate of the entire planet. One widely held theory says that the amount of carbon dioxide (CO 2 ) in the atmosphere is increasing as a result of burning various kinds of fuel. According to this theory, the atmosphere will heat up as a result of the increased carbon dioxide levels. How much? And how soon? These questions are studied by developing models and making predictions. The models are very involved, and consider many variables. In this project, we will look at just one of the variables: the number of automobiles in the U.S. This variable is used to predict how much gasoline is burned in the U.S., and that leads to predictions about the amount of carbon dioxide added to the atmosphere. In the table below are data on the number of automobiles in the U.S^1. The figures are in units of one million, so that in 1959 there were roughly 59,500,000 automobiles (rounded to the nearest hundred thousand). You should use Excel to complete the following explorations. The explorations will enable you to write a well-written report describing in detail your results. Include graphs as appropriate in the body of your report. It is this report that will be graded. (You should not turn in this sheet as part of your final report but you may wish to turn it in with a rough/preliminary draft.) Year Number of Automobiles 1959 59. 1964 72. 1969 86. 1975 106. 1979 118.
20 118. 1 Note the change in years is not the same each time
20 118.
purple box down until that box includes the value 36. These two points should be added to your graph. Ask for help if you have any trouble with this. Use this altered graph to explain why both of our models did such a poor job of predicting the number of automobiles after 1979.