Scatter Plots and Best Fitting Lines

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OBJECTIVES: S.ID.B.6 Summarize, represent and interpret data on two categorical and quantitative variables. Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. a. Fit a function to the data; use functions fitted to data to solve problems in the context of the data. c. Fit a linear function for a scatter plot that suggests a linear association. NQ.A.1 Reason quantitatively and use units to solve problems. Use units as a way to understand problems and to guide the solution of multi-step problems; choose and interpret units consistently in formulas; choose and interpret the scale and the origin in graphs and data displays. BIG IDEA: Relationships among quantities can be represented using tables, graphs, verbal descriptions and inequalities. Symbols are used to represent unknowns and variables. We can interpret and make critical predictions from functional relationships. PREREQUISITE SKILLS: students should understand how to plot points on the coordinate plane students should understand how to write and solve linear equations in two variables students should understand function notation VOCABULARY: 1. scatter plot: a graph with points plotted to show a possible relationship between two sets of data 2. correlation: describes a relationship between two data sets 3. positive correlation: a relationship between variables where as one variable increases, so does the other 4. negative correlation: a relationship between variables where as one variable increases, the other variable decreases 5. no correlation: no relationship between two variables 6. line of best fit: the line that best fits the data on a scatter plot SKILLS: create and interpret scatter plots use lines of best fit to make predictions _Notes Page 1 of 9 9/11/2014

REVIEW AND EXAMPLES: Scatter Plot: a graph of ordered pairs that show a possible relationship between two data sets. Correlation: the relationship between quantities as shown in a scatter plot *There are three types of linear correlation: Positive Correlation Negative Correlation Relatively No Linear Correlation *as x increases, *as x increases, *there is no linear relationship y also increases y decreases between x and y The correlation coefficient r, is a measure of the strength and direction of the linear relationship between two variables. If r = +1, then the data points If r = -1, then the data points The closer r is to 0, the less all fall on a perfectly straight all fall on a perfectly straight likely it is that there is a linear line with a positive slope. line with a negative slope. relationship between x and y. _Notes Page 2 of 9 9/11/2014

Best-Fitting Line: a line that best fits the pattern of the data in a scatter plot *If data have positive correlation, the slope of the best-fitting line will be positive. If data have negative correlation, the slope of the best-fitting line will be negative. If data have relatively no correlation, drawing a best-fitting line is not appropriate. Writing an Equation of a Best-Fitting Line Ex 1: Draw a scatter plot for the age and tail length of some tadpoles. Find the equation of the best-fitting line. Determine any correlation. Age (days) 5 2 9 7 12 10 3 6 Tail (mm) 14 15 3 8 1 3 12 9 Step One: Draw the scatter plot by plotting the ordered pairs on a coordinate grid. We will use the age in days as the horizontal axis, a, and the tail length as the vertical axis, t. Step Two: Sketch the best-fitting line. It should follow the general direction/pattern of the data and come close to all of the data points splitting them even above/below the line. Step Three: Pick two points on the best-fitting line and write the equation of the line using these two points (you can use points already in the data sets or add new points that fall on the line). Two points on the line are 3,14 and 10,3. The slope of the line is 14 3 11. 3 10 7 11. 7 Using point-slope form, we have an equation of the line as t 14 a 3 Rewriting in slope-intercept form, we have 11 33 11 131 t 14 a t a 7 7 7 7 Note: Depending on how you drew the best-fitting line, your equation may differ slightly. _Notes Page 3 of 9 9/11/2014

Step Four: Determine the type of correlation. The data have negative correlation because the slope of the best-fitting line is negative. The points do not fall on a perfectly straight line, so the correlation coefficient is somewhere between 0 and -1, closer to -1 since they are closer to a straight line than to a total scatter cloud. If you were asked to estimate r from the following values, which would be the best choice? r = 0.8, 0, -0.2, or -0.7 The best choice would be -0.7. Making Predictions with a Best-Fitting Line: Ex 2: In the tadpole example, predict how many days old a tadpole would be when its tail is 0 mm. Using the graph of the best-fitting line: It would take about 12 days for the length of a tadpole s tail to be 0 mm long. Ex 3: In the tadpole example, predict how long the tail would be when the tadpole is 7 days old. Using the equation of the best-fitting line: 11 131 t a 7 7 11 131 t (7) 7 7 77 131 t 7 7 54 t 7.7mm 7 _Notes Page 4 of 9 9/11/2014

Graphing Calculator Activity: Scatter Plots and Linear Regression Ex 4: Using the tadpole data, create a scatter plot on the graphing calculator and have it compute the best-fitting line using linear regression. Step One: Enter the data from the table into the Lists L1 and L2. On the home screen, choose STAT then Edit. To clear data from the lists, highlight the name of the list at the top of the column and press CLEAR. Then enter the ages in L1 and the tail lengths in L2. Step Two: On the home screen, use the following key strokes to calculate the best-fitting line (linear regression) and store it in Y1. Step Three: Graph the scatter plot with the best-fitting line. Go to the STAT PLOT menu by pressing 2 ND Y=. Choose the options shown in the screen shot. Use the same window as our graph above. Note: The calculator s equation of the line and the one we found earlier are fairly close. _Notes Page 5 of 9 9/11/2014

Distance (mi.) Algebra I Notes ASSESSMENT ITEMS: 1. Draw a scatter plot for the Women s Olympic 100-meter times since the year 1900. Find the equation of the best-fitting line. Determine any correlation. Predict the time of the women s 100-meter in the year 2000. Year (1900) 48 56 64 72 80 88 96 Time (sec) 11.9 11.5 11.4 11.1 11.1 10.5 10.9 SOLUTION: t = -0.02y + 12.9 ; There is a negative correlation. 10.9 seconds in the year 2000 2. Describe a real-life situation when a set of data would have a positive correlation. SOLUTION: answers may vary. Any situation where as x increases y also increases is correct. 3. The scatterplot below represents distances a walker traveled (in miles) versus time (in hours). 14 12 10 8 6 4 2 0 0 1 2 3 4 5 6 Time (hr.) Based on a linear model of the data, which choice below is the best prediction for the distance traveled after 4 hours? A. 2 miles B. 5 miles C. 8 miles D. 12 miles ANS: C _Notes Page 6 of 9 9/11/2014

Messages Remaining Algebra I Notes 4. Casey made a scatter plot to show the total number of text messages remaining on her plan throughout the month. 600 Text Message Use by Week 500 400 300 200 100 0 0 1 2 3 4 Number of Weeks Which linear equation best models Casey s data? A. y 500x 100 B. y 100x 500 C. y x 500 D. y 100x 500 ANS: D For #5-7, identify the correlation you would expect to see between each pair of data sets. 5. The temperature in Dallas and the number of cars sold in Philadelphia. A. positive correlation B. negative correlation C. no correlation ANS: C 6. The number of members in a family and the size of the family s grocery bill. A. positive correlation B. negative correlation C. no correlation ANS: A _Notes Page 7 of 9 9/11/2014

7. The number of times you sharpen your pencil and the length of your pencil. A. positive correlation B. negative correlation C. no correlation ANS: B 8. Based on the scatter plot, what would be the best estimation of the correlation coefficient, r? A. -0.8 B. 0 C. 0.4 D. 0.8 ANS: D 9. Rita had guests for dinner at her house eight times and has recorded the number of guests and the total cost for each meal in the table below. Graph a scatter plot of the data and determine the best-fitting line. Use the best-fitting line to predict the cost of dinner for 11 guests. Guests 3 4 4 6 6 7 8 8 Cost ($) 30 65 88 90 115 160 150 162 SOLUTION: c = 23.60g - 28.50 ; 11 guests would cost about $231 10. The scatter plot shows the number of orders placed for flowers before Valentine s Day at one shop. Based on this relationship, predict the number of flower orders placed on February 12. Solution: About 45 _Notes Page 8 of 9 9/11/2014

11. Which situation best describes a positive correlation? A. The amount of rainfall on Fridays. B. The height of a candle and the amount of time it has burned. C. The price of a pizza and the number of toppings added to it. D. The temperature of a cup of hot chocolate and the length of time it sits. ANS: C 12. Students graphed a scatter plot for the temperature of hot bath water and time if no new water was added. Which graph is incorrect? Explain the error. a. b. SOLUTION: Graph a is incorrect. The graph shows a positive correlation between time and water temperature. Temperature would go down as time passes, so the graph should be showing a negative correlation. _Notes Page 9 of 9 9/11/2014