By Samuel Chukwuemeka (Samdom For Peace) www.samuelchukwuemeka.com USING TECHNOLOGY TO DETERMINE SAMPLE LINEAR CORRELATION COEFFICIENT AND THE LEAST-SQUARES.

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Presentation transcript:

By Samuel Chukwuemeka (Samdom For Peace) USING TECHNOLOGY TO DETERMINE SAMPLE LINEAR CORRELATION COEFFICIENT AND THE LEAST-SQUARES REGRESSION LINE

 We shall use technology to determine the:  Sample Linear Correlation Coefficient or the Pearson Moment Correlation Coefficient and  Least-Squares Regression Line or the Line of Best Fit or the Linear Regression Equation  OBJECTIVES

 View my videos (where I did “hand” calculations) on:  Slope-Intercept Form  Sample Linear Correlation Coefficient or the Pearson Moment Correlation Coefficient and  Least-Squares Regression Line or the Line of Best Fit or the Linear Regression Equation  PRE-REQUISTES

 Windows-based Technology:  Pearson Statcrunch  Microsoft Excel  WHAT TECHNOLOGY SHALL WE USE?

 Consider the data:  Draw a scatter plot of your data  Compute the linear correlation coefficient to 3 d.p  Assume you add an additional point (10.4,9.3)  Draw the new scatter plot (with the additional point)  Compute the new linear correlation coefficient to 3 d.p  What are your observations? EXAMPLE 1 X Y

 The data below shows the number of days absent and the final grade for the students in a teacher’s class.  Find the least-squares regression line. Round to 2 d.p  Interpret the slope  Interpret the y-intercept  Predict the final grade for a student who misses one class period. Round to 2 d.p  Compute the residual  What are your observations?  Draw the least-squares regression line on a scatter diagram EXAMPLE 2 X(Absences)01234 Y (Final Grade)