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The normality assumption in linear regression is necessary to ensure the estimates of parameters are unbiased and the hypothesis testing…
n this post, we show how to generate random numbers into vector and matrix in R programming, from various statistical…
Linear regression is widely used to model the relationship between response or dependent variable and explanatory or independent variables. The…
When we do data analysis, random variables in the dataset are usually mutually correlated. Sometimes, we may want to measure…
When a correlation, usually Person type correlation, is calculated, two variables have to be continuous. But this requirement does not…
A Student t-distributed random variable is modeling the ratio between a standard Normal random variate and square root of a…
In hypothesis testing, the analyst has chance to commit both Type I and Type II errors. The Type I error…
In statistical hypothesis testing, there are usually two types of errors that the process will encounter, namely Type I and…