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A simple linear regression equation is to be constructed to determine if there is a linear relationship between a response variable (Y) and an explanatory variable (X). A random sample of size n has been collected and the values xi and yi for i = 1, 2, ..., n have been recorded. The residuals (ei) in this analysis are defined as the difference between the observed values of Y and the values of Y predicted by the regression equation.
The scatterplot or residual plots can be used to see if the regression equation is an appropriate model for the data. An assumption required for the simple linear regression equation to be valid is:
a) the residuals are constant
b) X and Y are independent
c) the variance of X is equal to the variance of Y
d) the relationship between X and Y is linear
Construct a histogram using the data. Identify the modal interval of the grouped data. Tracking risk (also called tracking error) is the standard deviation of the deviation of a portfolio's gross-of-fees total returns from benchmark return. Calcul..
Suppose that X1,..,Xn form a random sample from the normal distribution with unknown mean M and unknown standard deviation S, and let m and s denote the MLEs of M and S. for the sample size n=17, find a value of k such that P(m > M +ks) = 0.95
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What is the probability density function for this uniform distribution?
Researchers at the University of Washington and Harvard University analyzed records of breast cancer screening and diagnostic evaluations
Complete the ANOVA summary table for simple linear regression. -Conduct an F test for a significant regression and find bounds on the p value associated with this test.
q1. for each of the following state the null hypothesis and the alternative hypothesis.a the publisher of celebrity
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