(4) 9. b) For the following data use your calculator to determine the most appropriateempirical equation by comparing the correlation coefficient, r, values for thelinear, exponential and power model. Then state the empirical equation thatbest suits the data.Note: E = f(R)R371225326510050200448149997501825095800265980Linear r value:Exponential r value:Power r value:Empirical Equation:DELL

The regression equation is used to predict the value of dependent variable using one or more…

Answered: (4) 9. b) For the following data use…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A scientist, who wants to study the effects of precipitation on rice crops, sets up an experiment with 4 groups of rice crops. Rice crop harvest vs. precipitation level Group B Group A 0 150 Group C Precipitation (cm/annually) Harvest (pounds/acre) 0 60 Which statement best describes the relationship between the dependent and independent variables in this study? 20 O The amount of precipitation is dependent on the amount of rice harvest. O The amount of rice harvest is positively correlated with the increase in precipitation. The amount of rice harvest is not affected by the amount of precipitation. The amount of rice harvest is negatively correlated with the increase in precipitation. 200 Group D 40 300
Working as a professor, I may want to try and predict success on a final exam by student success on exam 1 and see whether or not there is a relationship between those. I gather data from a set of students and obtain their first exam score and their final exam score. Using the following data, find the Pearson’s r correlation coefficient, produce a linear regression equation, and describe the associated R2 value. First exam score (X) Final exam score (Y) 95 100 90 92 95 90 85 90 85 85 80 75 65 75 60 50 70 82 90 95 80 100 90 90 75 60 75 80 Pearson’s r = ______________ Is the r significant? _______________ Linear regression equation: ____________________
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
The following table shows students’ number of absences, x, and the student’s final grade,, y.# of absences x 6 2 15 9 12 5 8 Final grade y 82 86 43 74 58 90 78a) Calculate r, the correlation coefficient ________________b) Find the equation of the regression line __________________________________c) If a student is absent 4 times,, what grade does your regression line predict?__________________
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