How to find the sample Size

 


Comments

Post a Comment

Popular posts from this blog

Zero Inflated Poisson Distribution: What it is

Image
The zero-inflated Poisson distributio n is a mixture of a point mass at zero and a Poisson distribution. It is suitable when there is a significant number of zero values in the dataset, and a few datapoints have large values. This distribution allows for the excess of zeros and captures the occurrence of larger values. Intuition Imagine you have a dataset that represents the number of events that happen within a certain time or space, like the number of cars passing by a particular street in an hour. Usually, many hours will have no cars passing by, and only a few hours will have some cars passing by. The Zero-Inflated Poisson Distribution is a way to describe this kind of dataset. It combines two ideas to better represent the data: Lots of Zeroes : First, it acknowledges that many hours have no cars passing by. These zero counts are more common than any other number of cars. So, it considers two possibilities: either there are no cars at all (zero count) or the usual Poisson distrib...
Read more

How to Remember the Definition of Type I and Type II errors

 There are some clever mnemonics Type 1 error: Rejecting H0 when it is true Type II Error: Not rejecting H0 when it is false source1 Here are the mnemonics to remember: 1. Remember the story where the boy cried wolf  H0 : There is no wolf H1: There is a wolf data sample: Boy's cry Type I Error:  The first error the villagers made (when they believed him) was a type 1 error. Type II Error:  The second error the villagers made (when they didn't believe him) was a type 2 error 2. This has some truth in it. But can be ageism also Young scientists commit Type-I because they want to find effects and jump the gun while old scientist commit Type-II because they refuse to change their beliefs. 3.  A Type I error is a false POSITIVE; and P has a single vertical line. A Type II error is a false NEGATIVE; and N has two vertical lines. 4.  Type I errors are of primary concern Type II errors are of secondary concern 5. Remember RAAR, Reject when you should Accept ( type...
Read more