Describe your topic, provide your data, and cite your source. Collect at least 8 data points.

Curve-fitting Project – Linear Model (due at the end of Week 5)

Instructions

For this assignment, collect data exhibiting a relatively linear trend, find the line of best fit, plot the data and the line, interpret the slope, and use the linear equation to make a prediction. Also, find r2 (coefficient of determination) and r (correlation coefficient). Discuss your findings. Your topic may be that is related to sports, your work, a hobby, or something you find interesting. If you choose, you may use the suggestions described below.

A Linear Model Example and Technology Tips are provided in separate documents.

Tasks for Linear Regression Model (LR)

(LR-1) Describe your topic, provide your data, and cite your source. Collect at least 8 data points. Label appropriately. (Highly recommended: Post this information in the Linear Model Project discussion as well as in your completed project. Include a brief informative description in the title of your posting. Each student must use different data.)

The idea with the discussion posting is two-fold: (1) To share your interesting project idea with your classmates, and (2) To give me a chance to give you a brief thumbs-up or thumbs-down about your proposed topic and data. Sometimes students get off on the wrong foot or misunderstand the intent of the project, and your posting provides an opportunity for some feedback. Remark: Students may choose similar topics, but must have different data sets. For example, several students may be interested in a particular Olympic sport, and that is fine, but they must collect different data, perhaps from different events or different gender.

(LR-2) Plot the points (x, y) to obtain a scatterplot. Use an appropriate scale on the horizontal and vertical axes and be sure to label carefully. Visually judge whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different topic or data set.)

(LR-3) Find the line of best fit (regression line) and graph it on the scatterplot. State the equation of the line.

(LR-4) State the slope of the line of best fit. Carefully interpret the meaning of the slope in a sentence or two.

(LR-5) Find and state the value of r2, the coefficient of determination, and r, the correlation coefficient. Discuss your findings in a few sentences. Is r positive or negative? Why? Is a line a good curve to fit to this data? Why or why not? Is the linear relationship very strong, moderately strong, weak, or nonexistent?

(LR-6) Choose a value of interest and use the line of best fit to make an estimate or prediction. Show calculation work.

(LR-7) Write a brief narrative of a paragraph or two. Summarize your findings and be sure to mention any aspect of the linear model project (topic, data, scatterplot, line, r, or estimate, etc.) that you found particularly important or interesting.

You may submit all of your project in one document or a combination of documents, which may consist of word processing documents or spreadsheets or scanned handwritten work, provided it is clearly labeled where each task can be found. Be sure to include your name. Projects are graded on the basis of completeness, correctness, ease in locating all of the checklist items, and strength of the narrative portions.

“Choose an Olympic sport — an event that interests you. Go to http://www.databaseolympics.com/ and collect data for winners in the event for at least 8 Olympic games (dating back to at least 1980). (Example: Winning times in Men’s 400 m dash). Make a quick plot for yourself to “eyeball” whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different event.) After you find the line of best fit, use your line to make a prediction for the next Olympics (2014 for a winter event, 2016 for a summer event ).” That link will take you to the olympic database and i want to use soccer date back to 1980.

Thank you.

Answer

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xxx xxx of xxxx study is xx analyze xxx relationship between the number xx hours of study xxxxxx an exam xxx xxx exam xxxxxx xxx xxxx xxxxxx x simple random sample of xx xxxxxxx students was xxxxxxxxx xxx students xxxx xxxxx xxx xxxx hours they xxx xxxxxxx xxxxxx xx xxxx and the xxxxxxxxxx xxxxxx in that exam. xxx data xxxxxxxx xx xxxxx xx xxxxxxxx

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Student xx	xxxxx of Study	xxxx Score
1	4	xx
2	3	xx
3	x	75
4	5	xx
5	4	xx
6	6	86
7	x	42
8	x	66
x	x	xx
10	6	xx
xx	7	88
12	x	76
13	3	xx
xx	4	xx
15	5	72
16	3	xx
17	2	xx
xx	x	xx
xx	5	71
20	1	82
21	x	xx
22	x	xx
xx	5	xx
24	7	xx
25	3	xx

xxxx xxxxxxxxx xxxxxxx plot xxxxx the xxxx xxxxxx xxxxxx xxx number xx xxxxx xx xxxxx before xxx xxxxx

From the xxxxx scatter plot xx appears xxxx the data points xxxxxxx x xxxxxxxxxx linear xxxxxx xxx gradient of xxxx xxxxxxxxx xx xxxxxxxxx Thus xxxx the xxxxxxx xxxx xx xxxxxxx that xxxxx xx a direct linear

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Submitted by shri21 on Thu, 2016-02-04 06:28

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xxxxxxxx solutions xxx in xxx attached xxxxx Please xxxx xx work.

xx

xxx appears that xxxxxxx had xxxx xxxx xxxxxxxx xxxxxx xxxx earlier xxx x project. xxxxx why xxx got xxx xx xxxxxxxxxx xxxxxxx The xxxx which I xxxx to xxx was xx own and not xxxxxx xxxx somewhere.)

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xxxxxxxxxxxxx Project x Linear Model xxxx at xxx xxx of xxxx xxx

xxxxxxxxxxxxx

For xxxx xxxxxxxxxxx xxxxxxx data xxxxxxxxxx x relatively linear xxxxxx find xxx line of xxxx fit, plot the xxxx and xxx line, interpret xxx slope, xxx xxx xxx xxxxxx equation xx xxxx a prediction. xxxxx find r2 (coefficient xx determination) and x xxxxxxxxxxxx xxxxxxxxxxxxx Discuss xxxx findings. xxxx xxxxx xxx be that xx related xx sports, your xxxxx a xxxxxx xx xxxxxxxxx xxx find xxxxxxxxxxxx If you xxxxxxx xxx may use the suggestions described below.

A xxxxxx Model Example and Technology Tips xxx provided xx xxxxxxxx documents.

Tasks for Linear xxxxxxxxxx Model xxxxx

(LR-1) Describe xxxx xxxxxx xxxxxxx xxxx xxxxx and xxxx your source. Collect at xxxxx x data xxxxxxx Label appropriately. (Highly xxxxxxxxxxxx Post this information xx the xxxxxx xxxxx Project xxxxxxxxxx xx xxxx as xx your completed project. Include a brief informative description in the xxxxx xx xxxx xxxxxxxx Each

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