Returns the inverse of the left-tailed probability of the chi-squared distribution.
The chi-squared distribution is commonly used to study variation in the percentage of something across samples, such as the fraction of the day people spend watching television.
Returns the right-tailed probability of the chi-squared distribution.
The chi-squared distribution is associated with a chi-squared test. Use the chi-squared test to compare observed and expected values. For example, a genetic experiment might hypothesize that the next generation of plants will exhibit a certain set of colors. By comparing the observed results with the expected ones, you can decide whether your original hypothesis is valid.
Returns the chi-squared distribution.
The chi-squared distribution is commonly used to study variation in the percentage of something across samples, such as the fraction of the day people spend watching television.
Returns the inverse of the beta cumulative probability density function (BETA.DIST).
If probability = BETA.DIST(x,…TRUE), then BETA.INV(probability,…) = x. The beta distribution can be used in project planning to model probable completion times given an expected completion time and variability.
Returns the beta distribution. The beta distribution is commonly used to study variation in the percentage of something across samples, such as the fraction of the day people spend watching television.
Calculates the average (arithmetic mean) of a set of expressions evaluated over a table.
Returns the average (arithmetic mean) of the values in a column. Handles text and non-numeric values.
Returns the average (arithmetic mean) of all the numbers in a column.
Returns the approximate number of rows that contain distinct values in a column. This function can query large amounts of data with potentially better performance than DISTINCTCOUNT, with slight deviation from the exact result.
Adds calculated columns to the given table or table expression.