u 1.0 7.2 1 10 2.0 9.0 1.0 3.0 1 2.0 4.4 3.0 3.0 3.0 7.0 4.0 | 4.9 4.0 5.6 5.0 4.3 5.0 8.1 6.0 7.0 6.0 4.8 7.0 6.1 7.0 4.3 8.0 7.8 9.0 7.0 Figure 1 10.0 8.3 8.0 7.1 6.0 Figure 2 10.0 4.3 9.0 w m 1.0 3.8 2.0 5.8 1.0 10.0 14 10-x 2.0 9.0 3.0 8.1 3.0 8.0 4.0 9.2 4.0 | 7.0 5.0 10.3 5.0 6.0 6.0 9.7 6.0 5.0 7.0 9.8 7.0 4.0 8.0 3.0 9.0 2.0 Figure 4 10.0 1.0 8.0 7.9 9.0 6.6 Figure 3 10.0 3.7 Answer the following questions. The same response answer for more than one question. 1. Which data set has an apparent negative, but not perfect, linear relationship between its two variables? Choose one 2. In which data set is there evidence of a strong nonlinear relationship between the two variables? Choose one 3. Which data set indicates the strongest negative linear Choose one relationship between its two variables? 4. Which data set indicates a perfect positive linear relationship between its two variables? Choose one

u 1.0 7.2 1 10 2.0 9.0 1.0 3.0 1 2.0 4.4 3.0 3.0 3.0 7.0 4.0 | 4.9 4.0 5.6 5.0 4.3 5.0 8.1 6.0 7.0 6.0 4.8 7.0 6.1 7.0 4.3 8.0 7.8 9.0 7.0 Figure 1 10.0 8.3 8.0 7.1 6.0 Figure 2 10.0 4.3 9.0 w m 1.0 3.8 2.0 5.8 1.0 10.0 14 10-x 2.0 9.0 3.0 8.1 3.0 8.0 4.0 9.2 4.0 | 7.0 5.0 10.3 5.0 6.0 6.0 9.7 6.0 5.0 7.0 9.8 7.0 4.0 8.0 3.0 9.0 2.0 Figure 4 10.0 1.0 8.0 7.9 9.0 6.6 Figure 3 10.0 3.7 Answer the following questions. The same response answer for more than one question. 1. Which data set has an apparent negative, but not perfect, linear relationship between its two variables? Choose one 2. In which data set is there evidence of a strong nonlinear relationship between the two variables? Choose one 3. Which data set indicates the strongest negative linear Choose one relationship between its two variables? 4. Which data set indicates a perfect positive linear relationship between its two variables? Choose one

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Description: 1:49AAO www-awn.aleks.com: d on the same scalefrom a population,O REGRESSION AND CORRELATIONLinear relationship and the..yuV1.0 3.01.0 7.21110109-842.0 | 4.42.0 9.03.0 | 3.03.0 | 7.04.0 4.94.0 5.66-5.0 4.35.0 8.14.4-6.0 | 7.06.0 4.82.7.0 | 6.17.0 4.

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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1. Repeat the steps from tab #1 using this data to construct a scatter plot graph and calculate the correlation coefficient R. (Recall the correlation coefficient is R and not R2) Principals x Teachers y 77.8 43.7 78.4 43.8 80.8 45.0 80.5 45.6 R=0.997497 81.5 45.9 2. Does the R value represent a positive, negative or no correlation between the salaries of the teachers and principals? As teacher salaries increase, what happens to 84.8 48.2 87.7 49.3 prinicipal salaries? 91.6 51.3 93.6 52.9 3. Write the equation of the regression line for the data below. The equation is y= 95.7 54.4 95.7 54.2 4. Use the regression equation that you found in exercise #3 to predict the average annual salary of public school classroom teachers when the average annual salary of public school principals is $139,723. Show your work in the cells to the right. (Be careful when entering the x-value in the equation. The table shows numbers that have been adjusted in terms of the thousands. Example: if the salary…
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A researcher hypothesizes that ambient air carbon monoxide pollution levels at a certain location should be higher in the winter than they are in the summer. The reasoning behind this hypothesis is that a major source of carbon monoxide in the air is from the incomplete combustion of fuels, and fuels tend to burn less efficiently at low temperatures. Moreover, it is felt that the stagnant winter air is more likely to trap the pollution. In order to investigate this hypothesis, the data set in DS 9.7.12 is collected which shows the ambient air carbon monoxide pollution levels (parts per million) for ten Sunday mornings in the middle of winter and ten Sunday mornings in the middle of summer.