A high z -score means a very low probability of data above this z -score and a low z -score means a very low probability of data below this z -score.. So, a high z-score means the data point is many standard deviations away from the mean. A good first step would be good to plot a histogram or other density estimator and take a look at the distribution. The value of the z-score tells you how many standard deviations you are away from the mean. If a z-score is equal to 0, it is on the mean.
A positive z-score indicates the raw score is higher than the mean average. A negative z-score reveals the raw score is below the mean average. A high z -score means a very low probability of data above this z -score.
For example, the figure below shows the probability of z -score above 2. Probability for this is 0. The mean of the z-scores is always 0. The standard deviation of the z-scores is always 1.
The graph of the z-score distribution always has the same shape as the original distribution of sample values. The absolute value of z represents the distance between that raw score x and the population mean in units of the standard deviation.
The variance is now a lot smaller. Answer: It means the median of a series of data values representing a variable like temperature, pressure, volume, marks, mass, weight, cost, price, profit etc. You can usually determine the n by adding 1 to the degrees of freedom in an equation. In maths, the letter R denotes the set of all real numbers. In other words, real numbers are defined as the points on an infinitely extended line.
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