2.5 Oracle Machine Learning for SQL Statistical Functions
Various SQL statistical functions are available in Oracle Database to explore and analyze data.
A variety of scalable statistical functions are accessible through SQL in Oracle Database. These statistical functions are implemented as SQL functions. The SQL statistical functions can be used to compute standard univariate statistics such as MEAN
, MAX
, MIN
, MEDIAN
, MODE
, and standard deviation on the data. Users can also perform various other statistical functions such as t-test, f-test, aggregate functions, analytic functions, or ANOVA. The functions listed in the following table are available from SQL.
Table 2-5 SQL Statistical Functions Supported by OML4SQL
Function | Description |
---|---|
APPROX_COUNT |
Returns approximate count of an expression |
APPROX_SUM |
Returns approximate sum of an expression |
APPROX_RANK |
Returns approximate value in a group of values |
CORR |
Retuns the coefficient of correlation of a set of number pairs |
CORR_S |
Calculates the Spearman's rho correlation coefficient |
CORR_K |
Calculates the Kendall's tau-b correlation coefficient |
COVAR_POP |
Returns the population covariance of a set of number pairs |
COVAR_SAMP |
Returns the sample covariance of a set of number pairs. |
LAG |
LAG is an analytic function. It provides access to more than one row of a table at the same time without a self join.
|
LEAD |
LEAD is an analytic function. It provides access to more than one row of a table at the same time without a self join.
|
STATS_BINOMIAL_TEST |
STATS_BINOMIAL_TEST is an exact probability test used for dichotomous variables, where only two possible values exist.
|
STATS_CROSSTAB |
STATS_CROSSTAB is a method used to analyze two nominal variables.
|
STATS_F_TEST |
STATS_F_TEST tests whether two variances are significantly different.
|
STATS_KS_TEST |
STATS_KS_TEST is a Kolmogorov-Smirnov function that compares two samples to test whether they are from the same population or from populations that have the same distribution.
|
STATS_MODE |
Takes as its argument a set of values and returns the value that occurs with the greatest frequency |
STATS_MW_TEST |
A Mann Whitney test compares two independent samples to test the null hypothesis that two populations have the same distribution function against the alternative hypothesis that the two distribution functions are different. |
STATS_ONE_WAY_ANOVA |
Tests differences in means (for groups or variables) for statistical significance by comparing two different estimates of variance |
STATS_T_TEST_* |
The t-test measures the significance of a difference of means |
STATS_T_TEST_ONE |
A one-sample t-test |
STATS_T_TEST_PAIRED |
A two-sample, paired t-test (also known as a crossed t-test) |
STATS_T_TEST_INDEP and STATS_T_TEST_INDEPU |
A t-test of two independent groups with the same variance (pooled variances)
A t-test of two independent groups with unequal variance (unpooled variances) |
STDDEV |
returns the sample standard deviation of a set of numbers |
STDDEV_POP |
Computes the population standard deviation and returns the square root of the population variance |
STDDEV_SAMP |
Computes the cumulative sample standard deviation and returns the square root of the sample variance |
SUM |
Returns the sum of values |
DBMS_STAT_FUNCS
PL/SQL package is also available for users.
Parent topic: About the Oracle Machine Learning for SQL API