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In a regression analysis, if a new independent variable is added and R-squared increases and adjusted R-squared decreases precipitously, what can be concluded?
(a) The new independent variable improves the predictive power of the regression model.
(b)The new independent variable does not improve the predictive power of the regression model.
(c) The regression was performed incorrectly. It is impossible for R-squared to increase and adjusted R-squared decrease simultaneously.
(d) The new independent variable's coefficient is not significant at the 0.01 level.
A study was conducted with 35 people that resulted in a mean of 22.1 minutes with a standard deviation of 1.9 minutes. Using a .05 significance level, test the claim that the mean amount of time relief will be felt is less than 25 minutes.
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Once again, suppose that the standard deviation of the average or median is $5.00. Which is the probability that the average or median of the sample is greater than $22.50 but less than $25.00?
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For thefts involving more than $1,000, there is an inverse relationship between the value of the goods stolen and the length of the prison sentence given to the thief.
What type of situation would I be able to understand how to use regression as a key driver as an influence in sales or other outcomes?
Create an research question, and then state the experimental and null hypotheses. Then, explain why null and alternative hypotheses have to be mutually exclusive. Finally, discuss how Type I and Type II errors are related to your hypotheses.
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