NDK_MEANTEST

C/C++
.Net

int __stdcall NDK_MEANTEST	(	double *	X,
		size_t	N,
		double	target,
		double	alpha,
		WORD	method,
		WORD	retType,
		double *	retVal
	)

Calculates the p-value of the statistical test for the population mean.

Returns: status code of the operation

Return values

NDK_SUCCESS	Operation successful
NDK_FAILED	Operation unsuccessful. See Macros for full list.

Parameters

[in] X is the sample data (a one dimensional array).

[in] N is the number of observations in X.

[in] target is the assumed mean value. If missing, a default of zero is assumed.

[in] alpha is the statistical significance level. If missing, the default of 5% is assumed.

[in] method is the statistical test to perform (1=parametric).

[in]

retType

is a switch to select the return output:

Method	Value	Description
TEST_PVALUE	1	P-Value
TEST_SCORE	2	Test statistics (aka score)
TEST_CRITICALVALUE	3	Critical value.

[out] retVal is the calculated test statistics.

Remarks

The sample data may include missing values (NaN).
The test hypothesis for the population mean: \[H_{o}: \mu=\mu_o\] \[H_{1}: \mu\neq \mu_o\] Where:
- \(H_{o}\) is the null hypothesis.
- \(H_{1}\) is the alternate hypothesis.
- \(\mu_o\) is the assumed population mean.
- \(\mu\) is the actual population mean.
For the case in which the underlying population distribution is normal, the sample mean/average has a Student's t with T-1 degrees of freedom sampling distribution: \[\bar x \sim t_{\nu=T-1}(\mu,\frac{S^2}{T}) \] Where:
- \(\bar x\) is the sample average.
- \(\mu\) is the population mean/average.
- \(S\) is the sample standard deviation. \[ S^2 = \frac{\sum_{i=1}^T(x_i-\bar x)^2}{T-1}\]
- \(T\) is the number of non-missing values in the data sample.
- \(t_{\nu}()\) is the Student's t-Distribution.
- \(\nu\) is the degrees of freedom of the Student's t-Distribution.
The Student's t-Test for the population mean can be used for small and for large data samples.
This is a two-sides (i.e. two-tails) test, so the computed p-value should be compared with half of the significance level (\(\frac{\alpha}{2}\)).
The underlying population distribution is assumed normal (Gaussian).

Requirements

Header	SFSDK.H
Library	SFSDK.LIB
DLL	SFSDK.DLL

Examples

Namespace:	NumXLAPI
Class:	SFSDK
Scope:	Public
Lifetime:	Static

int NDK_MEANTEST	(	double[]	pData,
		UIntPtr	nSize,
		double	target,
		double	alpha,
		UInt16	argMethod,
		UInt16	retType,
		out double	retVal
	)