A researcher is studying the effect of 15 different variables on a measure of employee productivity....
QUESTION 1 Two different tests are designed to measure employee productivity and dexterity. Several employees are randomly selected and tested with these results. rod 1. Use the given data to find the equation of the regression line. Round the final values to three significant digits, if necessary 2. find the coefficient of correlationr 3. find the coefficient of determination2 4. find the standard error Se
Question 6 (10 marks) Finally, the researcher considers using regression analysis to establish a linear relationship between the two variables – hours worked per week and yearly income. a) What is the dependent variable and independent variable for this analysis? Why? (2 marks) b) Use an appropriate plot to investigate the relationship between the two variables. Display the plot. On the same plot, fit a linear trend line including the equation and the coefficient of determination R2 . (2 marks)...
The table below gives the number of hours ten randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line...
A researcher would like to predict the dependent variable Y from the two independent variables X1 and X2 for a sample of N=10 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level α=0.02. X1 X2 Y 40.5 62.9 21.8 16.4 51.3 31.8 62.5 44.4 29.6 60.4 53.6 40.6 50.2 54 33.7 39.2 51.5 37 80.9 16.9 58.1 41.6 52.6...
The table below gives the number of hours ten randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line...
A researcher would like to predict the dependent variable YY from the two independent variables X1X1 and X2X2 for a sample of N=12N=12 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level α=0.01α=0.01. X1X1 X2X2 YY 51.1 40.5 48 53.5 41 51.5 53.2 62.8 42.8 52.3 52.7 51.3 64.1 60 48.8 56.8 62.1 50 61.6 88.1 39.2 60.4 62.5...
The table below gives the number of hours five randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, y = bo + b x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate...
The table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, û = bo + b x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate...
The table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line...