Z- Score tutorial
Z- Score tutorial, welcome to the world of Z- score tutorial in Data Science. In this tutorial, one can learn about introduction of Z- score in data science with example. Are you the one who is looking forward to knowing the Z- score in Data science which comes under probability? Or the one who is very keen to explore the Z- score with examples that are available? Then you’ve landed on the right path which provides advanced Data Science training where all in-depth concepts will cover.
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Z Score in Data Science
A z-score indicates how many standard deviations a particular data point is from the mean of the data i.e.
- z-score of 1 means data point is One Standard Deviation from the Mean
- z-score of 2 means data point is Two Standard Deviation from the Mean.
- z-score of 3 means data point is Three Standard Deviation from the Mean.
- If a z-score is 0, it indicates that the data point’s score is identical to the mean score.
- z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
Z Score Formula:
Z Score Example
To answer this question, we can re-phrase it as: What percentage (or number) of students scored higher than Sarah and what percentage (or number) of students scored lower than Sarah? First, let’s reiterate that Sarah scored 70 out of 100, the mean score was 60, and the standard deviation was 15 (see below).
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