One-way Analysis of variance (ANOVA)

Description

The purpose of one-way ANOVA is to determine whether there is any statistically significant difference between the means of three more independent groups.

Usage

hanaml.OnewayAnova(conn.context,
                   data,
                   group = NULL,
                   sample = NULL,
                   multcomp.method = NULL,
                   significance.level = NULL)

Arguments

Value

• Statistics for each group: DataFrame
  structured as follows:
  - GROUP, type NVARCHAR(256), group name.
  - VALID_SAMPLES, type INTEGER, number of valid samples.
  - MEAN, type DOUBLE, group mean.
  - SD, type DOUBLE, group standard deviation.

• Computed results for ANOVA : DataFrame
  structured as follows:
  - VARIABILITY_SOURCE, type NVARCHAR(100), source of variability, including between groups, within groups (error) and total.
  - SUM_OF_SQUARES, type DOUBLE, sum of squares.
  - DEGREES_OF_FREEDOM, type DOUBLE, degrees of freedom.
  - MEAN_SQUARES, type DOUBLE, mean squares.
  - F_RATIO, type DOUBLE, calculated as mean square between groups divided by mean square of error.
  - P_VALUE, type DOUBLE, associated p-value from the F-distribution.

• Multiple comparison results: DataFrame
  structured as follows: - FIRST_GROUP, type NVARCHAR(256), the name of the first group to conduct pairwise test on.
  - SECOND_GROUP, type NVARCHAR(256), the name of the second group to conduct pairwise test on.
  - MEAN_DIFFERENCE, type DOUBLE, mean difference between the two groups.
  - SE, type DOUBLE, standard error computed from all data.
  - P_VALUE, type DOUBLE, p-value.
  - CI_LOWER, type DOUBLE, the lower limit of the confidence interval.
  - CI_UPPER, type DOUBLE, the upper limit of the confidence interval.
  

See Also

hanaml.OnewayAnovaRepeated

Examples

## Not run: 
Input DataFrame data:
> data
    GROUP  DATA
 0      A   4.0
 1      A   5.0
 2      A   4.0
 3      A   3.0
 4      A   2.0
 ...
 19     C   6.0
 20     C   7.0
 21     C   5.0
 Call OnewayAnova:
 > result <- hanaml.OnewayAnova(conn,
                                data,
                                multcomp.method = "tukey-kramer",
                                significance.level = 0.05)

 Expected output:
 > result[[1]]
      GROUP  VALID_SAMPLES         MEAN        SD
   0      A              8     3.625000  0.916125
   1      B              8     5.750000  1.581139
   2      C              6     6.166667  0.752773
   3    Total           22     5.090909  1.600866

## End(Not run)