A list of calculator directions is provided at the bottom of this text-box.
Context
The modern Olympic Games have changed dramatically since their inception in 1896. Are athletes getting better? We will use regression to investigate the change in winning times for one event—the men’s 1,500 meter race.
Variables
Year: the year of the Olympic Games, from 1896 to 2000.
Time: the winning time for the 1,500 meter race, in seconds.
Since the winning time depends on the year, the Year since 1896 is the explanatory variable, and the Winning time is the response variable.
Data
Download the olympicsLinks to an external site. datafile for the men’s 1,500 meter race. Then type the data into the graphing calculator. If you need a reminder about how to do this, review the list of Calculator directions below.
Prompt
In the first two questions below, you will use the calculator to produce and examine the scatterplot for the olympics datafile. You will also use a calculator to find the regression equation and correlation coefficient.
List of Directions
As you work through numbers 1) and 2) below, refer back to these directions when you need a quick reminder.
Create Your Math-Class Folder in Canvas (You only need to do this once.)
Directions: Entering (or Clearing) Data in a Calculator or Directions: Upload Calculator Data File to a TI Calculator
Upload Files to Your Math-Class Folder in Canvas
Embed Pictures in a Discussion Post (do not post attachments; please use these directions)
General Calculator Directions to Produce Scatterplot, LSR Line, & Regression Equation (All at the same time!
Flag question: Question 1
Question 1 3 pts
These directions assume that you have entered the olympics datafile into a calculator. If not, please see the Data section above.
Using the year since 1896 as the explanatory variable and the winning time as the response variable: graph the scatterplot with the regression line and produce the regression equation with the correlation coefficient (see Creating a Scatterplot in General Graphing Calculator Directions and then if using a TI calculator enter your equation in y= to see your equation and your scatterplot)
Notice that the data has a strong linear association, so it makes sense to use linear regression. (Always check the form of the scatterplot before using linear regression.)
Screenshot your scatterplot and regression line graphed together.
Save the .png file (the graph of your scatterplot and regression line) to your Math-Class folder.
Embed the .png file for your scatterplot and regression line in the text-box below.
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Flag question: Question 2
Question 2 3 pts
These directions assume you have produced the Simple linear regression results on your calculator. If not please see the previous question.
*For TI Calculators make sure you Turn Diagnostics On and then Find the Least Squares Regression Line to get the regression equation, correlation coefficient, and other statistics.
What is the Dependent Variable?
What is the Independent Variable?
What is your equation using the context of this problem?
What is the correlation coefficient?
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Flag question: Question 3
Question 3 2 pts
For which of the years 1900, 1940, or 2000 is the absolute prediction error the largest?
Group of answer choices
1900
1940
2000
Flag question: Question 4
Question 4 2 pts
For the year 1896, the winning time for the men’s 1500-meter race is an outlier. In what ways is this data point an outlier? Check all that apply
Group of answer choices
an outlier with respect to Y=Time
an outlier with respect to X=Year
an outlier with respect to the form of the relationship between X and Y
