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Curve-fitting project-linear model instructions

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Reference no: EM132854833

Curve-fitting Project - Linear Model Instructions 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).

Tasks for Linear Regression Model (LR)

(LR-1) Describe the topic, provide data, and cite source. Collect at least 8 data points. Label appropriately.

(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.

(LR-5) Find and state the value of r2, the coefficient of determination, and r, the correlation coefficient. 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) Make an estimate or prediction. Show calculation work.

Reference no: EM132854833

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