For least-squares to work well, we need: the relationship between x and y to be non-linear. residuals to be Uniformly distributed. the residuals to have a mean of zero. the residuals to be correlated with the explanatory variable.

A residual plot from a simple linear regression analysis is shown to the right. Use the plot to answer the question below. residuals 0 X Which of the following statements regarding the plot is true? OA. The condition that the residuals are normally distributed is not met since not all of the residuals fall on the reference line in the residual plot. OB. The condition that the residuals have constant variation is met since the lines connecting the largest positive residuals and largest negative residuals are parallel. Oc. The condition that the residuals are normally distributed is not met since there is a diamond shape to the residuals in the residual plot. OD. The condition that the residuals have constant variation is not met since the variation increases and then decreases as x gets larger.

Do not show any work on this question. For these ordered pairs: (0, 0.1), (1, 1), (2,2.4),(4,3.7), and (5, 5.7): Find (f ,y) and plot it as well as the five given points. Find the equation ofthe least squares regression line. Round off the x coefficient and the constant to the nearest onethousandth. Graph the equation together with the points above. If needed do not use a Pvalue to answer any problem. No credit will be given if a P value is used. Use only criticalvalues.

The following data is given: x -2 -1 0 1 2 y 1.5 3.2 4.5 3.4 2 Determine the coefficients a and b in the function y=a/(x2+b) that best fit the data. (Write the function in a linear form, and use linear least-squares regression to determine the value of the coefficients.) Once the coefficients are determined make a plot that shows the function and the data points.

A horizontal least squares regression line, implies that: Select one: a. The slope of the regression equation is 0 * b. None of the above is correct O c. The slope of the regression equation is positive d. The slope of the regression equation is negative

Find the least squares regression line for the data points. (Let x be the independent variable and y be the dependent varia (-1, 1), (1, -1), (3,-2) 2 X

In the graph shown below consider the horizontal line to represent the average y value for the data set and the slant line to represent the linear regression equation. use only the graph of the data to do the following: