Question regarding the explanatory variable
Indicate in a scatterplot what the data for your dependent variable and your explanatory variable would look like in a regression with an R2 equal to zero. How would this change if the regression R2 was equal to one?
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The yield of a chemical process is being studied. From previous experience with this process the standard deviation of yield is known to be 2.9. The past 5 days of plant operation have resulted in the following yields (given in percentages): 91.6,
A box of 40 components is called acceptable if it contains no more than 2 defectives. The procedure for sampling the box is to select 5 components at random and to reject the box if one or more defectives are found.
The mean breaking strength of yarn used in manufacturing drapery material is required to be at least 100 psi. Past experience has indicated that the standard deviation of breaking strength is 2.5 psi.
A political action committee wanted to estimate the proportion of county residents who support a change to the county leash law. They took a random sample of 600 county residents and found that the proportion who wanted to change the law was 34% w
Imagine that you had discovered a relationship that would generate a scatterplot very similar to the relationship Yi = Xi^2 , and that you would try to fit a linear regression through your data points.
Given the amount of money and effort that you have spent on your education, you wonder if it was (is) all worth it. You therefore collect data from the Current Population Survey (CPS) and estimate a linear relationship between earnings and the yea
Prove that the regression R2 is identical to the square of the correlation coefficient between two variables Y and X. Regression functions are written in a form that suggests causation running from X to Y. Given your proof, does a high regression
The foreman at a large plant estimates that there are defective parts about 1% of the time. If the plant produces 20,000 parts in a week, what is the variance for the number of defective parts?
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