semi-studentized residual

Hello, I have a question regarding the so-called "semi-studentized residual," which is of the form (e_i)* = ( e_i - 0 ) / sqrt(MSE). Here, e_i is the ith residual, 0 is the mean of the residuals, and sqrt(MSE) means the square root of MSE. Now, if I understand correctly, the population simple l

simple linear regression

I have two questions regarding simple linear regression that I was hoping someone could help me with. 1) According to what I have learned so far, the levels of X are "fixed," so that only Y is the random variable ( error is random as well). My question is, what if X is a random variable as well

normal approx. to binomial

Hello, I have a question regarding the so-called normal approx. to the binomial distribution. According to most textbooks I have looked at (these are undergraduate stats books), there is some talk of how a binomial random variable is approximately normal for large n, and may be approximated

elementary prob./stats concepts

According to a textbook I have, a random sample of n objects from a random variable X, is composed of n random variables itself, namely, X1,X2,...,Xn. I am having some difficulties in figuring out how to interpret this. For example, suppose that you are considering the population of adult males

probability definition

Hello, I have a question regarding the definition of probability. If I understand correctly, probability may be defined using just axioms. However, my textbook also uses a relative frequency definition, in which a probability is defined as being the proportion of times an outcome occurs in rep

basic stats question

Hello, I have a question regarding basic probability and statistics. If I understand correctly, the definition of independence holds for two events that are subsets of the same sample space. In other cases, we may need to construct a new sample space, such as with the flipping of a coin twice

95% confidence interval

Hello, I am currently taking a first course in statistics, and I was hoping that perhaps someone might be kind enough to answer a question for me. I understand that, while a quantitative variable may not be normally distributed, we may calculate the mean of the sample, and use facts about the