 Commands - Maple Help

Alphabetical List of Statistics Commands & Probability Distributions Commands

 Here is the list of all commands available in the Statistics package.

 compute the average absolute deviation generate agglomerated plots create area charts from data compute autocorrelations create bar charts from data generate biplots compute bootstrap statistics create box plots from data generate bubble plots cumulative distribution function central moments cumulant generating function characteristic function apply the chi-square test for goodness-of-fit apply the chi-square test for independence in a matrix apply the chi-square suitable model test create column graphs from data correlation/correlation matrix create autocorrelation plot from data compute number/total weight of observations compute number/total weight of missing values covariance/covariance matrix compute cross-correlations of two time series cumulants cumulant generating function cumulative distribution function compute cumulative products compute cumulative sums generate cumulative sum charts seven summary statistics deciles plot the density of a random variable remove any trend from a set of data compute lagged differences between elements create new distribution generate error plots evaluate data using floating-point arithmetic remove data items based on density compute expected values fit an exponential function to data apply exponential smoothing to a data set hazard (failure) rate Fisher information fit a model function to data five-point summary generate frequency plots frequency table geometric mean generate a grid of plots harmonic mean hazard (failure) rate generate heat maps generate histograms Hodges-Lehmann statistic statistical information display interactive interface to data analysis tools interquartile range inverse survival function join data samples estimate the probability density of a data set plot the kernel density estimate of a data set sample a kernel density estimate kurtosis robust linear regression likelihood function compute the likelihood ratio statistic apply linear filter to a data set fit a linear model function to data generate line charts fit a logarithmic function to data log likelihood function produce lowess smoothed functions generate a procedure for calculating statistical quantities compute the maximum likelihood estimate arithmetic mean average absolute deviation from the mean median compute the median absolute deviation moment generating function Mills ratio mode moments moment generating function compute moving averages for a data set compute moving medians for a data set compute moving statistics for a data set fit a nonlinear model function to data generate normal plots apply the one sample chi-square test for the population standard deviation apply the one sample t-test for the population mean apply the one sample z-test for the population mean generate a one-way ANOVA table order data items according to their ranks order statistics generate Pareto chart principal component analysis probability density function percentiles generate pie charts generate point plots fit a polynomial to data fit a power function to data fit a predictive linear model function to data principal component analysis compute the probability of an event probability density function probability function generate probability plots plot a profile of the likelihood function plot a profile of the log likelihood function quadratic mean compute quantiles generate quantile-quantile plots quartiles create new random variable range rank data items according to their numeric values remove data items satisfying a condition remove data items which belong to the given range remove non-numeric values robust linear regression Rousseeuw and Croux' Qn Rousseeuw and Croux' Sn generate random sample center and/or scale a set of data generate scatter plots generate 3D scatter plots statistical score generate scree plots for variance select data items satisfying a condition select data items which belong to the given range select non-numeric values apply Shapiro and Wilk's W-test for normality apply random permutation to a data sample skewness sort numeric data split matrix data into submatrices standard deviation standard error of the sampling distribution standardized moments generate sunflower plots support set of a random variable generate surface plots survival function generate symmetry plots compute data frequencies compute cumulative data frequencies generate tree maps trim data set trimmed mean apply the two sample F-test for population variances apply the paired t-test for population means apply the two sample t-test for population means apply the two sample z-test for population means variance coefficient of variation generate Venn diagrams create violin plots from data generate Weibull plots compute weighted moving averages for a data set winsorize data set winsorized mean Inventory of Probability Distributions

 Here is the list of continuous and discrete probability distributions as well as tools for creating new distributions.

 Bernoulli distribution beta distribution binomial distribution Cauchy distribution chi-square distribution discrete uniform distribution create a non-integer discrete distribution create new distribution empirical distribution Erlang distribution error (exponential power) distribution exponential distribution Fisher f-distribution gamma distribution geometric distribution Gumbel distribution hypergeometric distribution inverse Gaussian (Wald) distribution Laplace distribution logistic distribution log normal distribution Maxwell distribution Moyal distribution negative binomial (Pascal) distribution noncentral beta distribution noncentral chi-square distribution noncentral f-distribution noncentral t-distribution normal (Gaussian) distribution Pareto distribution Poisson distribution power distribution probability table Rayleigh distribution Student-t distribution triangular distribution uniform (rectangular) distribution von Mises distribution Weibull distribution