| Function | Description | Example | Result |
|---|---|---|---|
| avedev(list) | The average of the absolute deviations of values from their mean. | avedev(listx) for the data set {2, 2, 3, 4, 14} | 3.600 |
| average(list) | The average of the values of the list. | average(listx) for the data set {2, 2, 3, 4, 14} | 5.0000 |
| bfexp(listy, listx) | The B factor of the exponential regression for the lists. | ||
| bfexpnt(listy,listx) | The B factor of the exponent regression for the lists. | ||
| bfinv(listy,listx) | The B factor of the inverse regression for the lists. | ||
| bfln(listy, listx) | The B factor of the logarithmic regression for the lists. | ||
| bfpwr(listy, listx) | The B factor of the power regression for the lists. | ||
| binomdist(success, trials, probSuccess, formType) | Calculates the probabilities for a binomial distribution. | binomdist(3, 98, 0.04, 0) | 0.2 |
| combin(totalItems, groupSize) | The number of combinations of a subset of items. | combin(52, 5) | 2598960 |
| correl(listx, listy) | The correlation coefficient between two data sets. | correl(listy, listx) | |
| correlexp(listx, listy) | The correlation coefficient between two data sets using ln(y). | ||
| correlexpnt(listy,listx) | The correlation coefficient between two data sets using ln(y). | ||
| correlinv(listy,listx) | The correlation coefficient between two data sets using 1/x. | ||
| correlln(listx, listy) | The correlation coefficient between two data sets using ln(x). | ||
| correlpwr(listx, listy) | The correlation coefficient between two data sets using ln(x) and ln(y). | ||
| count(list) | The count of the values in the list. | count(listx) for the data set {2, 2, 3, 4, 14} | 5.0000 |
| covar(listx, listy) | The covariance of the product of paired deviations. | covar(listy, listx) | |
| devsq(list) | The sum of squares of deviations from the mean. | devsq(listx) for the data set {2, 2, 3, 4, 14} | 104.0000 |
| fact(x) | The factorial of a number, n!. | fact(5) | 120 |
| factdouble(x) | The double factorial of a number, n!!. | factdouble(10) | 3840 |
| forecast(xval, listx, listy) | Extrapolates future values based on existing x and y values using the linear regression model. | forecast(70,listy, listx) | |
| gamma(x) | The gamma function. | gamma(0.5) | 1.77 |
| gammaln(x) | calculates the natural logarithm of the absolute value of the gamma function of x. | gammaln(0.5) | 0.57 |
| geomean(list) | The geometric mean of the values of the list. | geomean(listx) for the data set {2, 2, 3, 4, 14} | 3.6768 |
| harmean(list) | The harmonic mean of the values of the list. | harmean(listx) for the data set {2, 2, 3, 4, 14} | 3.0216 |
| intercept(listx, listy) | Calculates the point at which a line will intersect the y values by using known x values and y values. | intercept(listy, listx) | |
| kurt(list) | The kurtosis of the values of the list, a measure of how peaked or flat a distribution is. | kurt(listx) for the data set {2, 2, 3, 4, 14} | 4.4630 |
| maxcorrelsqcurvefit(listy,listx) | Returns the curve fit with the maximum correlation squared. 0=error, 1=LIN, 2=LN, 3=EXP, 4=PWR, 5=EXPNT, 6=INV. | ||
| maxlist(list) | The maximum value of the list. | maxlist(listx) | |
| median(list) | The median of the values of the list. | median(listx) | |
| mfexp(listy, listx) | The M factor of the exponential regression for the lists. | ||
| mfexpnt(listy,listx) | The M factor of the exponent regression for the lists. | ||
| mfinv(listy,listx) | The M factor of the inverse regression for the lists. | ||
| mfln(listy, listx) | The M factor of the logarithmic regression for the lists. | ||
| mfpwr(listy, listx) | The M factor of the power regression for the lists. | ||
| minlist(list) | The minimum value of the list. | minlist(listx) | |
| mode(list) | The mode is the value that appears most often in a set of data. | mode(listx) for the data set {2, 2, 3, 4, 14} | 2.0000 |
| multinomial(list) | The factorial of the sum divided by the product of the factorials. | multinomial(listx) for the data set {2, 2, 3, 4, 14} | 3.089E11 |
| normdist(x, mean, stdev, mode) | Returns the density function or the normal cumulative distribution. | normdist(70, 63, 5, 1) | 0.92 |
| norminv(x, mean, stdev) | Returns the inverse of the normal cumulative distribution. | norminv(0.9192,63,5) | 70 |
| normsdist(x) | Returns the standard normal cumulative distribution function. | normsdist(1.0) | 0.84 |
| normsinv(x) | Returns the inverse of the standard normal cumulative distribution. | normsinv(0.8413) | 1 |
| permut(objects, elements) | The number of permutations for a given number of objects. | permut(52, 5) | 311875200 |
| poisson(events, average, type) | Returns the probability that a specific number of events will occur using the Poisson distribution. Type 1= CDF, 0 = PMF. | poisson(5, 4.25, 0) | 0.16482 |
| product(list) | Multiplies all the values of the list and returns the product. | product(listx) for the data set {2, 2, 3, 4, 14} | 672.0000 |
| rand() | Returns a random number between 0 and 1. The example used a seed of 1234. | rand() | 0.22 |
| randbetween(low,high) | Returns an integer random number between and including the integers of the low and high values. | randbetween(1,6) | |
| slope(listx, listy) | The slope of the linear regression line for the lists. | slope(listy, listx) | |
| srand(x) | Seeds the random number generator. The seed is valid until the application quits. Otherwise srandomdev() is called to generate a seed. | srand(-1234.56) | 1234 |
| stdev(list) | The sample standard deviation of the values of the list. | stdev(listx) for the data set {2, 2, 3, 4, 14} | 5.0990 |
| stdevp(list) | The population standard deviation of the values of the list. | stdevp(listx) for the data set {2, 2, 3, 4, 14} | 4.5607 |
| sum(list) | Sum of the values of the list. | sum(listx) for the data set {2, 2, 3, 4, 14} | 25.0000 |
| sumprod(list, list) | The sum of the products of the values of the lists. | sumprod(listy, listx) | |
| sumsq(list) | The sum of the squares of the values of the list. | sumsq(listx) for the data set {2, 2, 3, 4, 14} | 229.0000 |
| tdist(x,df,tails) | Returns the probability from the Student’s t‑distribution. tails = 1 or 2. | tdist(1.86, 8.0, 1) | 0.04996 |
| tinv(prob, df) | Returns the t value (a function of the probability and degrees of freedom) from the Student’s t‑distribution. | tinv(0.010, 8.0) | 3.355 |
| var(list) | The sample variance of the values of the list. | var(listy) for the data set {2, 2, 3, 4, 14} | 26.0000 |
| varp(list) | The population variance of the values of the list. | varp(listy) for the data set {2, 2, 3, 4, 14} | 20.8000 |