Please enable JavaScript.

Coggle requires JavaScript to display documents.

Z Scores: tells you how many standard deviations a value is above or below…

- - - - The mean of a z-score distribution is always 0 because z-scores measure how far each score is from the mean.
        
        Use z-scores to convert any distribution to a standardized distribution with a chosen mean and standard deviation. This makes different distributions easier to compare.
  - - - When all scores in a sample are changed into z-scores, the new z-score distribution keeps the same shape, has a mean of 0, and has a standard deviation of 1.
        
        A standardized distribution is a distribution of z-scores that always has a mean of 0 and a standard deviation of 1, regardless of the original distribution
        
        Transforming z-scores to a distribution with a predetermined mean and standard deviation means changing the z-scores so the new distribution has a specific mean and standard deviation while keeping the same overall shape.
        
        Inferential statistics use information from a sample to make conclusions or answer questions about a population.
        
        A z-score shows where an X value is located in a distribution. A positive z-score means the score is above the mean, while a negative z-score means it is below the mean. The number tells how many standard deviations the score is from the mean.
      - The distribution of sample z-scores has the same shape as the original sample of scores.