Descriptive Stats
- Arithmetic mean
- Standard deviation
(n-1)
- Standard deviation
(n)
- Standard error
- Skewness
- Kurtosis
- 95% confidence
limit for mean
- 99% confidence
limit for mean
- Min value
- Max value
- Sample range
- Number of samples
- Median
- Sx
- Sx2
- Geometric mean
- Variance
- Average deviation
- Angular Descriptive
Stats
- Cosine mean
- Sine Mean
- Mean vector length
- Mean angle Cosine
- Mean angle Sine
- Mean angle Tan
- Mean angle
- Circular variance
- Angular variance
- Angular deviation
- Circular standard
deviation
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Parametric Tests
- Frequency analysis
- Unpaired t-test
- Paired t-test
- Unequal variance t-test
- Bonferroni t-test
- One-way non-repeated
ANOVA
- One-way repeated
ANOVA
- Two-way replicated
ANOVA
- Two-way repeated
ANOVA
- Three-way ANOVA
- Linear regression
- Multiple linear
regression
- Compare two
observed values
- Compare 2 sample
proportions
- Compare sample and
population
- Compare paired
proportions
- Bartlett's test
- Dunnett's test
- Duncan's test
- Tukey's test
- General N factor
ANOVA for multiple fixed effects factors
- 2k factorial design
for k=2,3
- Durbin-Watson test
(residual auto correlation test)
- Single
classification ANCOVA for completely randomized
design
- Pearson R
- Repeated measures
linear regression
- Backward
elimination for multiple linear regression
- Polynomial
regression.
- Tigonometric
regression.
- Linear-linear
correlation
- Angular-angular
correlation
- Angular-linear
correlation
- Rayleigh test
determine if oberved samples of angular data have
a tendency to cluster around a given angle
indicating a lack of randomness of the
distribution)
- Single Factor
analysis of variance for angular data
- Link-Wallace test
for multiple com-parisons of k population means
- Hotelling's T-square
test for two series of population means
- Dixon test for
outliers
- F-test for the
overall mean of K subpopulations (ANOVA)
- F-test for multiple
comparisons of contrasts between K population
means
- F-test for K
population means (ANOVA)
- Z-test of a
correlation coefficient
- Z-test of 2
correlation coefficients
- t-test of a
correlation coefficient
- Hartley's test for
equality of K variances
- Fisher cumulant
test for normality of a distribution.
- F-test for two
population variances
- Z-test for
correlated proportions
- The w/s test for
normality of a population
- Cochran test for
variance outliers
- Chi-square test for
compatibility of K counts
- Cochran test for
consistency in an nxk table of dichotomous data.
- Chi-square test for
consistency in a 2xk table
- Chi-square test for
independence in a pxq table
- Sign test for a
median
- Sign test for two
medians (paired observations)
- Signed rank test
for a mean
- Signed rank test
for two mean (paired observations)
- Mardia-Watson-Wheeler
test (to test whether two independent random
samples from circular observations differ
significantly from each other regarding mean
angle, angular variance or both)
- Harrison-Kanji-Gadsden
test
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Nonparametric Tests
- NxK Chi-squared
- 2x2 Chi-squared
- Fisher's exact test
- McNemar's test
- One-sample chi-squared
- Cramer's V
- Contingency
coefficient
- Wilcoxon's matched
pairs
- Mann-Whitney U-Test
- Friedmann's test
- Kruskal-Wallis test
- Spearman rank
correlation
- Kendall rank
correlation
- Kendall partial
rank correlation
- Kendall coefficient
of concordance
- LogRank test
- Mantel-Haenszel
test
- Kolmogorov-Smirnov
test
- Phi-coefficient for
2x2 tables
- Cramer coefficient
C
- Median test
- Extension of the
median test
- Robust rank order
test
- Siegel-Tukey test
for scale differences
- Moses rank-like
test for scale differences.
- Cochran Q-test.
- Jonckheere test for
ordered alternatives
- Page test for
ordered alternatives
- Chi-square test for
k independent samples
- Kendall coefficient
of agreement u
- Kappa statistic for
nominally scaled data.
- Gamma statistic for
ordered variables
- Lambda statistic
for asymmetrical association
- Somers d for
asymmetrical association of ordered variables
- Cox's F-test
- Fisher's cumulant
test for normality of a distribution.
- F-test for two
counts (Poisson distribution).
- Wilcoxon inversion
(U) test
- Median test of two
populations
- Median test of k
populations
- The Siegal-Tukey
rank sum dispersion test of two variances
- Steel test for
comparing K treatments with a control
- Sequential test for
a population mean
- Sequential test for
a standard deviation
- Adjacency test for
randomness of fluctuations
- Serial correlation
test for randomness of fluctuations
- Turning point test
for randomness of fluctuations
- The difference sign
test for randomness in a sample
- Run-test on
successive differences for randomness in a sample
- Run-test for
randomness of two related samples
- Run-test for
randomness in a sample
- Wilcoxon-Mann-Whitney
rank sum test for randomness of signs
- Friedmann's test
for multiple treatment of a series of subjects
- Rank correlation
test for agreement in multiple judgements
- Test the equality
of multinomial distributions
- Bowker test for
nominal-scale data
- Lehmacher test for
variables with more than 2 categories
- Fisher contingency
table test for variables with more than two
categories
- Gehan test for
censored data
- Fisher-Pitman
randomization test for interval-scale data
- Pitman-Welch test
for interval scale data
- Wall test for
nominal scale data
- Pitman
randomization test for interval scale data
- Angular-angular
correlation
- Watson U2 test (To
test whether two samples from circular
observations differ significantly from each
other, regarding mean direction or angular
variance
- Watson-Williams
test (to test whether the mean angles of two
independent circular observations differ
significantly from each other)
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Data Transforms
- Polynomial
- Reciprocal
- Natural Log
- Log10
- Log2
- Ln(x+1)
- Exp(x)
- Square Root
- Cube Root
- Xn
- Sin
- Cos
- Tan
- Sort Ascending
- Sort Descending
- Rank Ascending
- Rank Descending
- Modulo
- Absolute Value
- Standardize
- Center
- Multiply columns
- Divide columns
- Add columns
- Subtract columns
- Error function
- Complementary error
function
- Logit
- Probit
- Normit
- Normal probabilites
- Student's t
probabilities
- F distribution
probabilities
- Chi-Squared
probabilities
- Transform by a
spreadsheet formula
- Matrix operations:
inverse matrix, transpose Matrix
- Sinh
- Cosh
- Tanh
- aSin
- aCos
- aTan
- Bessel functions of
first and second kind
- Conversions
- Integer ceiling,
floor
- Powerful language
to program user-defined transforms
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Graphics
- Pie chart
- Bar chart
- Area graph
- Line graph
- Scatter graph
- Box-whisker graph
- 3D surface graph
- Bubble charts
- Polar charts
- Radar charts
- Polynomial
regression plot
- Pareto chart option
in frequency analysis plots
- Kaplan-Meier
survival curves
- Density function
plots and cumulative probability plots for
Gaussian (Normal) distribution, lognormal
distribution, Weibull distribution, gamma
distribution, Poisson distribution, beta
distribution and chi-square distribution
- Regression plots
direct from raw data (single factor, single
factor repeated measures)
- Polynomial
regression plots
- One-factor response
curves and two-factor response surface plots(1st
and 2nd order)
- Minimum spanning
tree plots for 2 dimensions
- Levey-Jennings/Shewart
Charts
- Sequential test for
a population mean
- Sequential test for
a standard deviation classification
- c-chart
- X-chart
- R-chart
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Miscellaneous
- Generate uniformly
distributed random numbers
- Generate normal
randomly distributed numbers
- Generate Poisson
randomly distributed numbers
- Generate
exponentially distributed numbers
- Generate gamma
randomly distributed numbers
- Fill range with
arithmetic sequence
- Fill range with
geometric sequence
- Fill range with
constant
- Kolmogorov-Smirnoff
test for goodness of fit (to investigate the
difference between an observed distribution and a
specified population distribution)
Quality
control
- The sequential test
for a dichotomous classification
- Quality control
acceptance sampling
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