MDM4U: Data Project - Linear Regression Analysis Due: May 14, 2012
Total Page:16
File Type:pdf, Size:1020Kb
MDM4U: Data Project - Linear Regression Analysis Due: May 14, 2012
Name:
Task: Investigate an Olympic event and use linear regression analysis to predict the winning time/distance/weight for future games. Present your findings in a neatly formatted report.
Olympic Gold Medal – Event:
1. Research the results (gold medal winner only) for your event from its inception up to and including the 2004 games (summer) or 2006 games (winter). Present this data in a table. 2. Graph a scatterplot of the data using Excel. Describe the overall trend in the data (classify the linear correlation.) 3. Are there any unusual points, trends, or variations from the trend? Explain what and/or why these points/trends may have occurred. 4. Use Excel to determine the Least Squares Regression Line of Best Fit for the data set. Superimpose the line on your graph. 5. Write the equation of your least-squares line. Record the correlation coefficient, r, and discuss its meaning. 6. What does the slope of your line indicate, specifically with respect to your event? 7. Use your model to predict the winning value (time/distance/weight) in the 2008/2010 Olympics. Compare your result to the actual winning value and calculate the residual. Evaluate your model’s prediction strength. 8. Add the data point for 2008/2010 to your original data set. Run another linear regression and record your model and the correlation. Use your new model to predict the winning value for the next Olympics.
EVALUATION:
0: not done 1: does not meet expectations 2: approaching expectations 3: meets expectations 4: exceeds expectations
Complete and accurate data presented in legible table format? 0 1 2 3 4 Scatter plot clear, appropriate scale, correctly and well labeled? 0 1 2 3 4 Discussion of unusual points, trends? 0 1 2 3 4 LSRL, plot on graph, r? 0 1 2 3 4 Correct discussion of slope? 0 1 2 3 4 Correct use of model to predict 2008/2010? 0 1 2 3 4 Calculation of residual, comparison and evaluation of model? 0 1 2 3 4 New LSRL with 2012/2014 prediction? 0 1 2 3 4 Overall neatness and presentation, style, spelling, grammar? 0 2 4 6 8
Total = / 40 = /10
Comments: