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Question: Web-based exercise. The best way to develop some feeling for how a regression line fits the points on a scatterplot is to use an applet that allows you to plot and move data points and watch the least-squares line move as the points change. Go to the Statistics: Concepts and Controversies Web site, www.whfreeman.com/scc7e, and look at the Correlation and Regression applet. Click in the "Show least-squares line" box to see the regression line. Where should one place or move points to in order to have the largest effect on the least-squares line?
if an analysis of variance is used for the following data what would be the effect of changing the value of ss1 to
the revenues of the top eleven personal computer manufacturers are given in hundred millions15 17 23 26 27 35 72 88 91
Refer to Grocery retailer Problem 6.9. Assume that regression model (6.5) for three predictor variables with independent normal error terms is appropriate.
Does the normal distribution yield a good approximation of the actual results?
The sample mean was found to be 194 pounds with a standard deviation of 11.2 pounds. What percentage of men have weights between 175 and 2235 pounds?
use the one-proportion z-interval procedure to find the required confidence interval. be sure to check the conditions
question a population has a standard deviation of 50. a random sample of 100 items from this population is selected.
Analysis of variance (ANOVA) is used to determine if there is a difference between the means of different populations. This is an example from a student in Prescott Arizona.
What is the rejection point at α = .10 and indicate if you would accept or reject H o ?
Multiple choice questions based on regression - dependent variable Y and an independent variable X is provided.
If that point were removed from the data, would the correlation become stronger or weaker? Explain.- If that point were removed from the data, would the slope of the regression line increase or decrease? Explain.
Compute correlation loading coefficients using (a) the correlation matrix, and (b) the covariance matrix. How do the two sets of coefficients compare to each other? Are both sets equally informative? Explain (see also Exercise 3.23).
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