| HP Stat Pac 1 |
 |
|
| 01 - Mean, Standard Deviation, Standard Error |
Given a set of data points, this program computes the following statistics:
mean x̅, standard deviation sx or sx', standard error of the mean sx̅ or sx̅' |
 |
02 - Mean, Standard Deviation, Standard Error
(Grouped Data) |
Given a set of data points grouped by occurrence, this program computes the following statistics:
mean x̅, standard deviation sx or sx', standard error of the mean sx̅ or sx̅' |
|
| 03 - Permutation and Combination |
This program computes permutations mPn and combinations mCn,
where m, n are integers and 0 ≤ n ≤ m. |
|
04 - Arithmetic, Geometric, Harmonic and
Generalized Means |
Given a set of data points, this program computes the following means:
arithmetic mean A, geometric mean G, harmonic mean H, generalized mean M(t)
|
|
| 05 - Sums For Two Variables |
This program computes sums for a set of given data { (xi,yi), i = 1, 2, ..., n }. |
|
| 06 - Basic Statistics (Two Variables) |
This program computes mean, standard deviation, covariance, and correl- ation coefficient derived
from a set of data points { (xi,yi), i = 1, 2, ..., n }. |
|
| 07 - Moments, Skewness and Kurtosis |
This program computes moments for a set of given data. |
|
| 08 - Random Number Generator |
This program calculates uniformly distributed random numbers ui in the range 0 ≤ ui ≤ 1,
or normally distributed random numbers ni with mean m and standard deviation σ. |
|
| 09 - Analysis of Variance (One Way) |
The one-way analysis of variance tests the differences between the population means of k treatment groups. |
|
10 - Normal Distribution
Rev. Aug 16, 2016
|
This program computes the Gaussian probability density function f(x) and the cumulative density function Φ(x). |
|
| 11 - Inverse Normal Integral |
This program determines the boundary x of the cumulative density function such that Q(x) yields a given value. |
|
| 12 - Chi-Square Distribution |
This program evaluates the chi-square density f(x), where x ≥ 0. |
|
| 13 - t Distribution |
This program evaluates the integral for t distribution I(x,ν), where x > 0. |
|
| 14 - F Distribution |
This program evaluates the integral of the F distribution Q(x) for given values of x (>0). |
|
| 15 - Bivariate Normal Distribution |
This program evaluates the bivariate normal distribution f(x,y). |
|
| 16 - Logarithmic Normal Distribution |
If X is a random variable whose logarithm is normally distributed with mean m and variance σ²,
then X has a logarithmic normal distribution with density function f(x), where x > 0. This program computes f(x) and the following statistics for given m, σ²:
median, mode, mean, variance. |
|
| 17 - Weibull Distribution |
For the Weibull distribution, this program can be used to find f(x), Q(x), and x for a given Q, 0 < Q < 1. |
|
| 18 - Binomial Distribution |
This program evaluates the binomial density function f(x) for given p and n. |
|
| 19 - Negative Binomial Distribution |
This program evaluates the negative binomial density function f(x) for given p and r. |
|
| 20 - Hypergeometric Distribution |
This program evaluates the hypergeometric density function f(x) for given a, b and n. |
|
| 21 - Poisson Distribution |
This program evaluates the density function f(x) and the cumulative distribution P(x). |
|
| 22 - Linear Regression |
This program fits a straight line y = a₀ + a₁x to a set of data points { (xi,yi),
i = 1, 2, ..., n } by the least squares method. |
|
| 23 - Exponential Curve Fit |
This program computes the least squares fit of n pairs of data points { (xi,yi), i = 1, 2, ..., n },
where yi > 0, for an exponential function of the form y = a ebx (a > 0) |
|
| 24 - Power Curve Fit |
This program fits a power curve y = axb (a>0) to a set of data points { (xi,yi),
i = 1, 2, ..., n }, where xi > 0, yi > 0. |
|
| 25 - Logarithmic Curve Fit |
This program fits a logarithmic curve y = a + b ln(x) to a set of data points
{ (xi,yi),
i = 1, 2, ..., n }, where xi > 0, yi > 0. |
|
| 26 - Least Squares Regression |
This program determines the coefficients c, d of the equation y = cxa + dxb
for a set of data points { (xi,yi), i = 1, 2, ..., n }, where a, b are any given real numbers and xi > 0 for i = 1, 2, ..., n. |
|
| 27 - Multiple Linear Regression |
For a set of data points { (xi,yi,zi), i = 1, 2, ..., n } this program fits a
linear equation of the form z = a₀ + a₁x + a₂y by the least squares method. |
|
| 28 - Parabolic Curve Fit |
For a set of data points { (xi,yi), i = 1, 2, ..., n } this program fits a parabola y = a₀ + a₁x + a₂x². |
|
| 29 - Paired t Statistic |
This program computes the test statistic t for a set of paired observations from two normal populations with means µ₁, µ₂ (unknown). |
|
| 30 - t Statistic For Two Means |
Suppose { x₁, x₂, .., xn₁ } and { y₁, y₂, .., yn₁ } are independent random samples from two normal
populations having means µ₁, µ₂ (unknown) and the same unknown variance σ².
This program tests the null hypothesis H₀: µ₁ - µ₂ = D |
|
| 31 - Chi-Square Evaluation |
This program calculates the value of the χ² statistic for the goodness of fit test. |
|
| 32 - 2 x k Contingency Table |
Contingency tables can be used to test the null hypothesis that two variables are independent. |
|
| 33 - Bartlett's Chi-Square Statistic |
The χ² computed by this program has a chi-square distribution (approximately) with k - 1 degrees of freedom
which can be used to test the null hypothesis that s₁², s₂², ... , sk² are all estimates of the same population variance σ². |
|
| 34 - Spearman's Rank Correlation Coefficient |
Spearman's rank correlation coefficient rs uses n (the number of paired observations (xi,yi))
and Di, defined as rank(xi) - rank(yi) = Ri - Si. |
|
| 35 - Mann-Whitney Statistic |
This program computes the Mann-Whitney test statistic U on two independent samples of equal or unequal sizes.
This test is designed for testing the null hypothesis of no difference between two populations. |
|
| 36 - Kendall's Coefficient of Concordance |
Suppose n individuals are ranked from 1 to n according to some specified characteristic by k observers,
the coefficient of concordance W measures the agreement between observers (or concordance between rankings). |
|
| 37 - Biserial Correlation Coefficient |
The biserial correlation coefficient rb is used where one variable Y is quantitatively measured
while the other continuous variable X is artificially dichotomized (that is, artificially defined by two groups). It measures the degree of linear association between X and Y. |
|
