STAT201 USC EWA Guessed & Actual Distance Lab Session 4

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User Generated

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Nfqs1415

Subject

Mathematics

School

University Of South Carolina

Description

Please look at the files that have all the information and instruction for writing this paper, it should be about 3 to 4 pages.

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Simple linear regression results: Dependent Variable: var2 Independent Variable: var1 var2 = 21.054663 + 0.65314944 var1 Sample size: 10 R (correlation coefficient) = 0.97461152 R-sq = 0.94986761 Estimate of error standard deviation: 20.721917 Parameter estimates: Parameter Estimate Std. Err. Alternative DF T-Stat P-value Intercept 21.054663 8.5423799 ≠ 0 8 2.4647304 0.039 Slope 0.65314944 0.0530512 ≠ 0 8 12.311681 x variable is Guessed Distances and y variable is True Distances. Overlay function of x: type x Overlay function of x: Build X о This adds a line representing the line y = x. Note that this line is not the line of best fit. This line represents where the data would have fallen if you were a perfect guesser. • Copy this scatterplot with the superimposed line y = x to a Word document. 4. Answer the following question from the lab book: Describe any patterns you see in your raw scatter plot. Is the relationship linear? Or, does it seem to describe a curve? Are there any points that seem to depart from the pattern of the others (outliers)? It seem to describe a Curve 5. Answer the following question from the lab book: Look at how the points on your scatter plot lie in relation to the y=x line. Are they scattered evenly above and below the line? If yes, you are approximately an unbiased guesser. (This is rare). If most of the points lie below the y=x line, you tend to overestimate the distance: you are positively biased. If most of the points lie above the y=x line then you underestimate distances and are negatively biased. What type of guesser are you? guessen Proximately an unbiased Use StatCrunch to perform a simple linear regression analysis: Stat -> Regression -> Simple Linear -> x= guessed distances and y= true distances. Place a copy of the output generated (both screens) into Word. Copy all output provided (Simple Linear regression output and scatter plot with line of best fit - not the same as the one in the first scatter plot, y = x). 7. Using the output from the simple linear regression fill in the following table: Prediction of 11th Landmark Prediction Equation Y=21.05 + 0.65 Guessed Distance to 11th Landmark 80 Predicted Distance to 11th Landmark Y=21.05 +0.65 (80) = 73.5 True Distance to 11th Landmark 100 feet = 73.5 Residual of 11th Landmark 26.5 a. 8. Misc. questions to answer: Give the value of the correlation coefficient and describe the relationship between the two quantitative variables using this measurement (talk about strength and direction). 8.97 b. Give the value of r-squared and interpret it as it was done in the lecture videos. R-5%=0.94 c. Interpret the slope as it was done in the lecture videos. 0.65 d. Interpret the y-intercept as it was done in the lecture videos and note if the interpretation is meaningful (regardless interpret it). Before you leave make sure the lab instructor has given you credit for this lab so you will get 9 points for Lab 4 in the gradebook. MAKE SURE YOU SAVE AN ELECTRONIC COPY OF YOUR OUTPUT AS YOU WILL NEED IT IN THE PAPER (ewa).
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