Cola izquierda
Less than
Adds all probability to the left of a boundary.
Locate values, calculate areas under the normal curve or find the value corresponding to a percentile.
Choose a question and work with original X values or directly with Z.
The same distribution can answer different questions depending on the shaded area.
Cola izquierda
Adds all probability to the left of a boundary.
Cola derecha
Measures the proportion above a boundary.
Central area
Subtracts the cumulative probabilities at the upper and lower boundaries.
Dos colas
Adds the regions below and above the two boundaries.
The Z-score converts any normal distribution to a scale with mean 0 and standard deviation 1. This lets you compare values measured in different units.
z = (x − mean) / standard deviation
The calculator assumes that the variable follows a normal distribution. It does not test normality or determine whether a result is good, bad or clinically relevant.
A Z-score indicates how many standard deviations a value is from the mean. A positive Z is above the mean and a negative Z is below it.
The sign indicates the side of the mean. The magnitude indicates distance: Z = 1.5 means 1.5 standard deviations above it; Z = -1.5 means the same distance below it.
The percentile approximates the percentage of the distribution to the left of a value. The 90th percentile leaves about 90% of values below it.
Choose Calculate probability, select Less than or Greater than, and enter the boundary. If you are using X values, add the mean and standard deviation.
Select Between and enter a lower and upper boundary. The calculator subtracts the cumulative probabilities at the two boundaries.
Choose Find a value, enter the percentile and, when using X, the mean and standard deviation. The critical Z is calculated first and then converted to the original scale.
In a continuous distribution, the probability of one exact value is zero. Therefore, less than and less than or equal to produce the same probability.
No. The tool calculates results under a normal-distribution assumption, but it does not run a normality test on your data.