Statistical Functions

This function returns the confidence interval for the expected value of a random variable using a Student’s *t*-distribution. Syntax CONFIDENCE.T(alpha; standard_dev; size) Arguments alpha(required): The significance level used to calculate the confidence interval. The confidence level is 100*(1 – alpha)%, meaning an alpha of 05 corresponds

This function calculates the margin of error for a confidence interval around a sample mean, assuming a normal distribution and a known population standard deviation. The confidence interval is: Confidence Interval=xˉ±CONFIDENCE.NORM() where: xˉ = Sample mean. The interval has a 100×(1−α)%100×(1−α)% confidence level (e.g., 95% for α=0.05α=0.05). Syntax CONFIDENCE.NORM(alpha; standard_dev; size)

This function returns the inverse of the right-tailed chi-square (χ²) distribution, providing the critical value where: If probability = CHISQ.DIST.RT(x, df), then CHISQ.INV.RT(probability, df) = x. Syntax CHISQ.INV.RT(probability; degrees_freedom) Purpose Used in hypothesis testing to: Determine critical values for χ² tests (e.g., goodness-of-fit, independence). Validate whether observed

This function performs a chi-square (χ²) test of independence, returning the p-value associated with the test statistic. It compares observed frequencies (actual_range) against expected frequencies (expected_range) to determine if there is a statistically significant association between categorical variables. Syntax CHISQ.TEST(actual_range; expected_range) Arguments Argument

This function returns the inverse of the left-tailed chi-squared (χ²) distribution. Given a probability (cumulative probability), it finds the corresponding χ² value (x) such that: If probability = CHISQ.DIST(x; df; TRUE), then CHISQ.INV(probability; df) = x. Used to determine critical values for hypothesis testing (e.g., goodness-of-fit

This function returns the minimum number of successes (k) in a binomial distribution where the cumulative probability is ≥ a specified threshold (alpha). It is the inverse of BINOM.DIST(). Syntax BINOM.INV(trials; probability_s; alpha) Key Use Case: Quality Control: Determine the maximum allowable defective items in a

This function calculates probabilities for a binomial distribution, which models scenarios with: A fixed number of trials (trials). Only two outcomes per trial: success or failure. Independent trials with a constant success probability (probability_s). Syntax BINOM.DIST(number_s; trials; probability_s; cumulative) Example Use Case: Calculating the probability that 50 out of 100 people support a

This function returns the inverse of the beta cumulative distribution. Given a probability, it finds the corresponding value x such that: If probability = BETA.DIST(x, …), then BETA.INV(probability, …) = x. Syntax BETA.INV(probability; alpha; beta; [A]; [B]) Common Use Case: In project planning, it estimates completion

This function returns values of the cumulative beta distribution, which is commonly used to analyze variance across samples (e.g., modeling proportions like daily computer usage time). Syntax: BETA.DIST(x; alpha; beta; cumulative; [A]; [B]) Arguments: x (required): The value (between A and B) to evaluate. alpha (required):

This function calculates the average of cells that meet multiple specified criteria. Syntax: AVERAGEIFS(average_range; criteria_range1; criteria1; [criteria_range2; criteria2]; …) Arguments: average_range (required): The range of cells to average (must contain numeric values). criteria_range1 (required): The first range to evaluate against criteria1. criteria1 (required): The condition

This function calculates the average of all cells in a range that meet a specified criterion. Syntax: AVERAGEIF(range; criteria; [average_range]) Arguments: range (required): The range of cells to evaluate against the criteria. These can include numbers, names, arrays, or references. criteria (required):

This function calculates the average of the values in an argument list. Unlike AVERAGE(), it includes not only numbers but also text and logical values (TRUE and FALSE) in the calculation. Syntax: AVERAGEA(value1; [value2] …) Arguments: value1(required) and value2 (optional): At least one and up

This function returns the average (arithmetic mean) of the arguments. To calculate the average, interval-scaled variables are summed and then divided by their count. Syntax AVERAGE(number1, number2, …) Arguments number1 (required) and number2 (optional): At least one and up to 255 arguments (30 in Excel

This function returns the average of the absolute deviations of data points from their mean. The function calculates the arithmetic mean of the deviations of a data set based on the average, excluding the sign. Syntax: AVEDEV(number1, number2, …) AVEDEV() is