1.AVEDEV

Purposes: to return a set of data with the average absolute deviation of the average, this function can be measured data (for example, a student examination results) of the dispersion.

Syntax: AVEDEV (number1, number2 ,…)

Parameters: Number1, number2, … are used to calculate the average absolute deviation of a set of parameters, the number can be between 1 to 30.

Example: If A1 = 79, A2 = 62, A3 = 45, A4 = 90, A5 = 25, while the formula “= AVEDEV (A1: A5)” to return to 20.16.

2.AVERAGE

Purposes: the calculation of the arithmetic mean of all parameters.

Syntax: AVERAGE (number1, number2 ,…)。

Parameters: Number1, number2, … is to calculate the average of 1 to 30 parameters.

Example: If A1: A5 region named Score, in which numerical 100,70,92,47 and 82, respectively, then the formula “= AVERAGE (Score)” to return to 78.2.

3.AVERAGEA

Purposes: the list of calculated parameters of the average value. AVERAGE function with not only the difference between the figures, and text and logical values (such as TRUE and FALSE) are also involved in the calculation.

Syntax: AVERAGEA (value1, value2 ,…)

Parameters: value1, value2, … as the need to calculate the average of the 1-30 cells, or numerical range.

Example: If A1 = 76, A2 = 85, A3 = TRUE, the formula “= AVERAGEA (A1: A3)” to return to 54 (that is, 76 +85 +1 / 3 = 54).

4.BETADIST

Purposes: to return to the cumulative distribution function Beta function. Beta cumulative distribution function is usually used to study samples of the collection of certain things and the changes occurred. For example, it is time to watch television a day rate.

Syntax: BETADIST (x, alpha, beta, A, B)

Parameters: X used for calculating the value function to be living in an optional upper and lower bounds of (A and B) between. Alpha distribution parameters. Beta distribution parameters. A value x is the optional lower bound of their interval, B is the numerical range of x-owned optional upper bound.

Example: the formula “= BETADIST (2,8,10,1,3)” to return to .685470581.

5.BETAINV

Purposes: to return to the cumulative beta distribution function of the inverse function. That is, if the probability = BETADIST (x ,…), then BETAINV (probability ,…)= x. beta cumulative distribution function can be used for project design, completion expected in the given time and changes in the parameters, the simulation of possible completion time.

Syntax: BETAINV (probability, alpha, beta, A, B)

Parameters: Probability distribution for the Beta probability value, Alpha parameter distribution, Beta distribution of parameters, A value x of the optional lower bound of their interval, B Numerical x-owned sector, the range of options.

Example: the formula “= BETAINV (0.685470581,8,10,1,3)” to return to 2.

6.BINOMDIST

Purposes: to return a dollar value of the binomial probability distribution. BINOMDIST function for a fixed number of independent experiments, the results of the experiment contains only two kinds of success or failure of the situation, and the probability of success in the fixed during the experiment. For example, it can calculate the objects being thrown from a coin 10 times, when a positive probability of upward 6.

Syntax: BINOMDIST (number_s, trials, probability_s, cumulative)

Parameters: Number_s for the number of successful experiments, Trials for the number of independent experiments, Probability_s for the first time the probability of success of the experiment, Cumulative is a logical value used to determine the form of function. If cumulative is TRUE, then return to BINOMDIST function cumulative distribution function, that is up to the probability of successful number_s; If FALSE, the return probability density function, that is, the probability of successful number_s.

Example: the results of coin throwing is a positive rather than negative, throwing coins for the first time the probability of positive is 0.5. The objects being thrown from a coin 10 times in the formula for calculating the 6th for the “= BINOMDIST (6,10,0.5, FALSE)”, the results of calculation of mean 0.205078

7.CHIDIST

Purposes: to return to c2 one-tailed probability distribution. c2 distribution associated with the c2 test. Can be compared using the c2 test observations and expectations. For example, assume that the next generation of a plant genetics experiment show a group of colors displayed. Use this function comparison of observations and expectations, to determine the validity of initial assumptions.

Syntax: CHIDIST (x, degrees_freedom)

Parameters: X is used to calculate the distribution of one-tailed probability of c2 values, Degrees_freedom is the degree of freedom.

Example: the formula “= CHIDIST (1,2)” mean that the calculated results .606530663.

8.CHIINV

Purposes: to return to c2 one-tailed probability distribution of the inverse function. If the probability = CHIDIST (x,?), While CHIINV (probability,?) = X. Use this function comparison of observations and expectations, to determine the validity of initial assumptions.

Syntax: CHIINV (probability, degrees_freedom)

Parameters: Probability distribution for the c2 one-tailed probability, Degrees_freedom for freedom.

Example: the formula “= CHIINV (0.5,2)” to return to 1.386293564.

9.CHITEST

Purposes: to return to the relevance of testing the value, that is, the statistical distribution of the return value of c2 and the corresponding degree of freedom, you can use the assumption that the value of c2 test to determine whether they were confirmed by experiments.

Syntax: CHITEST (actual_range, expected_range)

Parameters: Actual_range is included in the data observations, Expected_range summary is included in the ranks of the product and the ratio of the total value of the data.

Example: If A1 = 1, A2 = 2, A3 = 3, B1 = 4, B2 = 5, B3 = 6, the formula “= CHITEST (A1: A3, B1: B3)” to return to .062349477.

10.CONFIDENCE

Purposes: to return to the overall average confidence interval, which is the average of either side of the sample area. For example, a class of students take the exam, in accordance with a given confidence level, the examination can determine the minimum and maximum scores.

Syntax: CONFIDENCE (alpha, standard_dev, size).

Parameters: Alpha is used to calculate the confidence level (which is equivalent to 100 * (1-alpha)%, if the alpha of 0.05, the confidence level of 95%) a significant level of parameters, Standard_dev data standard deviation of the overall region, Size sample capacity.

Example: Suppose 46 samples from the test scores of students, their average is divided into 60, the overall standard deviation for 5 minutes, the average sub-region in the following 95% confidence level. The formula “= CONFIDENCE (0.05,5,46)” to return to 1.44, that is, test scores for the 60 ± 1.44 minutes.

11.CORREL

Uses: array1 and array2 range the return of the correlation coefficient between. Two different things it can determine the relationship between, for example, testing students in physics and mathematics association between academic performance.

Syntax: CORREL (array1, array2)

Parameters: Array1 first group of numerical range. The second group Array2 numerical range.

Example: If A1 = 90, A2 = 86, A3 = 65, A4 = 54, A5 = 36, B1 = 89, B2 = 83, B3 = 60, B4 = 50, B5 = 32, while the formula “= CORREL (A1 : A5, B1: B5) “the return of 0.998876229, we can see that A, B 2 has a higher degree of data related to each other.

12.COUNT

Purposes: to return to the figures of the number of parameters. It can be an array or range of statistics on the number of cells containing numbers.

Syntax: COUNT (value1, value2 ,…)。

Parameters: value1, value2, … are various types of data contained or referenced parameters (1 ~ 30), of which only the number of types of data can be statistical.

Example: If A1 = 90, A2 = the number of, A3 = “”, A4 = 54, A5 = 36, while the formula “= COUNT (A1: A5)” to return to 3.

13.COUNTA

Purposes: to return to parameter group in Central Africa the number of null value. COUNTA function can be calculated using the array or range in the number of data items.

Syntax: COUNTA (value1, value2 ,…)

Description: value1, value2, … have to count the value of the number of parameters for the 1 ~ 30. In this case the parameters can be of any type, including spaces but does not include blank cells. If the parameter is the array or cell reference, then the array or reference cell of the blank will be ignored. If you do not need the logic of the value of statistics, text or error values, you should use the COUNT function.

Example: If A1 = 6.28, A2 = 3.74, the rest of the cell is empty, then the formula “= COUNTA (A1: A7)” equal to 2, the calculated results.

14.COUNTBLANK

Purposes: the calculation of a range in the number of blank cells.

Syntax: COUNTBLANK (range)

Parameters: Range for the need to calculate the number of blank cells in the region.

Example: If A1 = 88, A2 = 55, A3 = “”, A4 = 72, A5 = “”, the formula “= COUNTBLANK (A1: A5)” to return to 2.

15.COUNTIF

Use: calculation of the region to meet the conditions of a given number of cells.

Syntax: COUNTIF (range, criteria)

Parameters: Range for the requirements to meet the conditions in which the number of cell range. Criteria to determine which cells will be taken into account the conditions, which may take the form of digital, or text expression.

16.COVAR

Purposes: to return to covariance, that is, each pair of data points the average deviation of the product. Using covariance of two data sets to study the relationship between.

Syntax: COVAR (array1, array2)

Parameters: Array1 is the first integer data contained in the range, Array2 is the second contained in range of an integer data.

Example: If A1 = 3, A2 = 2, A3 = 1, B1 = 3600, B2 = 1500, B3 = 800, while the formula “= COVAR (A1: A3, B1: B3)” to return to 933.3333333.

17.CRITBINOM

Purposes: to return to the cumulative binomial distribution so that greater than or equal to the minimum threshold, the result can be used for quality inspection. For example, decided to allow a maximum number of defective parts, we can guarantee that when the entire product when leaving the assembly line passing inspection.

Syntax: CRITBINOM (trials, probability_s, alpha)

Parameters: Trials is the number of Bernoulli trials, Probability_s is a test of the probability of success, Alpha is the threshold.

Example: the formula “= CRITBINOM (10,0.9,0.75)” to return to 10.

18.DEVSQ

Purposes: to return a sample of data points with their average and the square of the deviation.

Syntax: DEVSQ (number1, number2 ,…)

Parameters: Number1, number2, … are used to calculate the deviation sum of squares of 1-30 parameters. They can be comma-separated values, can also be an array reference.

Example: If A1 = 90, A2 = 86, A3 = 65, A4 = 54, A5 = 36, while the formula “= DEVSQ (A1: A5)” to return to 2020.8.

19.EXPONDIST

Purposes: to return to exponential distribution. This function can create events of the time interval between the models, such as estimates of the automatic bank teller machines to pay a cash amount of time spent in order to determine the process of one-minute maximum sustained probability of occurrence.

Syntax: EXPONDIST (x, lambda, cumulative).

Parameters: X value function, Lambda parameter values, Cumulative Index to determine the logic value function. If cumulative is TRUE, EXPONDIST to return to the cumulative distribution function; If cumulative is FALSE, the return probability density function.

Example: the formula “= EXPONDIST (0.2,10, TRUE)” to return to 0.864665, = EXPONDIST (0.2,10, FALSE) to return to 1.353353.

20.FDIST

Purposes: to return to the probability distribution F, it can determine the existence of the two data series of different changes in extent. For example, through the analysis of a class of boys and girls of the test scores to determine the extent of the changes in scores of girls and boys are different.

Syntax: FDIST (x, degrees_freedom1, degrees_freedom2)

Parameters: X is used to calculate the probability distribution of the interval point, Degrees_freedom1 molecular degrees of freedom, Degrees_freedom2 is the denominator degrees of freedom.

Example: the formula “= FDIST (1,90,89)” to return to .500157305.