Statistical Functions

The STDEVA() function estimates the standard deviation based on a sample. It is used to measure how dispersed or spread out values are from their mean (average). Unlike STDEV.S(), the STDEVA() function includes text and logical values in the calculation:

The STDEV.P() function calculates the standard deviation based on an entire population. The standard deviation is a statistical measure that quantifies how much values in a dataset deviate from the mean (average). A low standard deviation indicates that values are

The STANDARDIZE() function returns the standardized value (also called the z-score) of a data point from a distribution defined by a known mean and standard deviation. A standardized value represents how far and in what direction a given value deviates

Returns the k-th smallest value in a dataset. This function is useful for extracting values with specific relative rankings without sorting the data. Syntax: SMALL(array; k) Arguments: array(required): The range or array containing the dataset k(required): The ordinal position of

The SLOPE() function returns the slope of the linear regression line that best fits the data points in the arrays known_y’s and known_x’s. The slope represents the rate of change — that is, the vertical change divided by the horizontal

The SKEW() function returns the skewness of a distribution. Skewness measures the degree of asymmetry of a distribution around its mean. A positive skewness indicates a distribution with a tail that extends toward more positive values. This is also referred

This function returns the square of the Pearson correlation coefficient (r²) based on paired data points (known_y’s and known_x’s). The r² value represents the proportion of variance in the dependent variable (y) that can be explained by the independent variable

This function returns the rank of a number within a list of numbers. The rank indicates the number’s relative size compared to other values in the list. If the list were sorted, the rank would correspond to the number’s position.

Returns the rank of a specified number within a dataset, using average ranking for tied values. Unlike RANK() which skips subsequent ranks for duplicates, this function assigns the average rank to all identical values. Syntax: RANK.AVG(number; ref; [order]) Arguments Argument Description number (required) The numeric

Returns the rank of a specified number within a dataset, indicating its relative size compared to other values. The rank represents the number’s position if the dataset were sorted. Syntax: RANK(number; ref; [order]) Arguments Argument Description number (required) The value to

Returns the specified quartile of a dataset. Quartiles divide data into four equal groups, useful for analyzing income distributions, sales performance, or survey results (e.g., identifying the top 25% of values). Syntax: QUARTILE(array ; quart) Arguments Argument Description array (required) Range of

This function calculates the probability of values falling within a specified range. If no upper limit is provided, it returns the probability of values equaling the lower limit exactly. Syntax: PROB(x_range; prob_range; lower_limit; [upper_limit]) Arguments: x_range(required): The set of possible

This function calculates probabilities for a Poisson-distributed random variable. The Poisson distribution is commonly used to predict the frequency of rare, independent events over a specific interval (e.g., call center arrivals per hour or tire failures per 100,000 miles). Syntax:

This function returns the number of possible permutations when selecting *k* elements from a set of *n* elements. A permutation is an arrangement where the order of elements matters. Syntax: PERMUT(number; number_chosen) Arguments: number (required): The total number of elements (*n*). number_chosen (required): The number of elements

This function returns the rank of a value (alpha) in a dataset as a percentage, ranging from 0 to 1 (inclusive). It can be used to evaluate the relative position of a value within a dataset. For example, you can use PERCENTRANK.INC() to