@deftypefn {Function} {} PDF.NEGBIN (@var{x}, @var{n}, @var{p})
@deftypefnx {Function} {} CDF.NEGBIN (@var{x}, @var{n}, @var{p})
@deftypefnx {Function} {} RV.NEGBIN (@var{n}, @var{p})
-Negative binomial distribution with number of successes paramter
+Negative binomial distribution with number of successes parameter
@var{n} and probability of success parameter @var{p}. Constraints:
integer @var{n} >= 0, 0 < @var{p} <= 1, integer @var{x} >= 1.
@end deftypefn
containing boxplots for all the factors.
If /COMPARE=VARIABLES is specified, then one plot per factor is produced, each
each containing one boxplot per dependent variable.
-If the /COMPARE subcommand is ommitted, then PSPP uses the default value of
+If the /COMPARE subcommand is omitted, then PSPP uses the default value of
/COMPARE=GROUPS.
The ID subcommand also pertains to boxplots. If given, it must
Identical to INITIAL and EXTRACTION.
@end itemize
-If /PLOT=EIGEN is given, then a ``Scree'' plot of the eigenvalues will be printed. This can be useful for visualising
+If /PLOT=EIGEN is given, then a ``Scree'' plot of the eigenvalues will be printed. This can be useful for visualizing
which factors (components) should be retained.
The /FORMAT subcommand determined how data are to be displayed in loading matrices. If SORT is specified, then the variables
NPAR TESTS
/KOLMOGOROV-SMIRNOV (normal 3.5 2.0) = @var{score} @var{age}.
@end example
-If the variables need to be tested against different distributions, then a seperate
+If the variables need to be tested against different distributions, then a separate
subcommand must be used. For example the following syntax tests @var{score} against
a normal distribution with mean of 3.5 and standard deviation of 2.0 whilst @var{age}
is tested against a normal distribution of mean 40 and standard deviation 1.5.
@menu
-* One Sample Mode:: Testing against a hypothesised mean
+* One Sample Mode:: Testing against a hypothesized mean
* Independent Samples Mode:: Testing two independent groups for equal mean
* Paired Samples Mode:: Testing two interdependent groups for equal mean
@end menu
@subsection One Sample Mode
The @cmd{TESTVAL} subcommand invokes the One Sample mode.
-This mode is used to test a population mean against a hypothesised
+This mode is used to test a population mean against a hypothesized
mean.
The value given to the @cmd{TESTVAL} subcommand is the value against
which you wish to test.
@end display
@cindex Cronbach's Alpha
-The @cmd{RELIABILTY} command performs reliablity analysis on the data.
+The @cmd{RELIABILTY} command performs reliability analysis on the data.
The VARIABLES subcommand is required. It determines the set of variables
upon which analysis is to be performed.
@section ROC
@vindex ROC
-@cindex Receiver Operating Characterstic
+@cindex Receiver Operating Characteristic
@cindex Area under curve
@display
UNIMPL_CMD ("CATREG", "Categorical regression")
UNIMPL_CMD ("CCF", "Time series cross correlation")
UNIMPL_CMD ("CLEAR TRANSFORMATIONS", "Clears transformations from active dataset")
-UNIMPL_CMD ("CLUSTER", "Hierachial clustering")
+UNIMPL_CMD ("CLUSTER", "Hierarchical clustering")
UNIMPL_CMD ("CONJOINT", "Analyse full concept data")
UNIMPL_CMD ("CORRESPONDENCE", "Show correspondence")
UNIMPL_CMD ("COXREG", "Cox proportional hazards regression")
UNIMPL_CMD ("GET TRANSLATE", "Read other file formats")
UNIMPL_CMD ("GGRAPH", "Custom defined graphs")
UNIMPL_CMD ("GRAPH", "Draw graphs")
-UNIMPL_CMD ("HILOGLINEAR", "Hierarchial loglinear models")
+UNIMPL_CMD ("HILOGLINEAR", "Hierarchical loglinear models")
UNIMPL_CMD ("HOMALS", "Homogeneity analysis")
UNIMPL_CMD ("IGRAPH", "Interactive graphs")
UNIMPL_CMD ("INFO", "Local Documentation")
UNIMPL_CMD ("MODEL LIST", "Show existing models")
UNIMPL_CMD ("MODEL NAME", "Specify model label")
UNIMPL_CMD ("MULTIPLE CORRESPONDENCE", "Multiple correspondence analysis")
-UNIMPL_CMD ("MULT RESPONSE", "Multiple reponse analysis")
+UNIMPL_CMD ("MULT RESPONSE", "Multiple response analysis")
UNIMPL_CMD ("MVA", "Missing value analysis")
UNIMPL_CMD ("NAIVEBAYES", "Small sample bayesian prediction")
UNIMPL_CMD ("NLR", "Non Linear Regression")