Stat-200 - 数据统计软件

注：特此通知，BIOSOFT将于2022年12月31日停止交易。

电子邮件地址info@biosoft.com将在该日期后的2年内继续有效，以便向软件的注册用户提供程序激活代码和少量技术支持。

Stat - 200是综合的统计数据包。它的客户在处理，分析和呈现数据所需描述性统计，参数和非参数统计测试，图形和数据转换。Stat -200中的参数测试和程序总共60个，有66个非参数测试和程序以及30个不同的描述性统计。

ANOVAN因子分析。不寻常的程序，例如，生存分析。测试有相关的信息窗口，提供文献参考和事实，以帮助获得正确的工作。概率是直接计算的，因此要使用表格。

Stat-200用户界面，其统计和绘图模块都可以从逻辑树视图中选择。您经常使用的程序可以放在收藏夹列表中以便即时访问。工作簿是操作和选择数据的工具。它可以是大小，受您的计算机硬件限制。提供了65种数据转换，并且内置了高等语言，以便用户可以对转换进行编程。数据可以键入，也可以电子表格中复制，粘贴或拖放。此外，可以直接打开多种格式的电子表格文件。Stat-200很与数据库，它ODBC数据库连接的Recordset表，使数据和结果可以的来回传递。

Stat-200中的图形类型统计数据的常用类型，如线条，饼图，条形图，散点图和盒须图以及3D绘图选项。提供多种线图样式，拟合多项式，对数，指数和幂函数以及移动平均线图，以及原始数据，均值和数据频率图，此外还可以自动绘制图形类型，如Kaplan-Meier , Weibull , Pareto , Shewart , Polar等。

测试的数字结果可以直接从Stat-200打印或复制到剪切板或保存以导入程序中。图形可以直接打印或保存，也可以导出为Windows位图或Windows图元文件。通过HTML的可选输出结果以及.JPG和.PNG文件格式的图形结果，增强了与Web的。

Stat-200的统计功能模块作为OCX提供，可以嵌入到网页或脚本语言中，这为将统计分析作为类型醒目的一部分纳入了很大的空间。

英文简介：

Stat-200 is a remarkably comprehensive general statistics package. It incorporates all the descriptive statistics, parametric and non-parametric statistical tests. graphics and data transforms you will need for processing, analyzing and presenting data. Parametric tests and procedures in Stat-200 total 60 and there are 66 non-parametric tests and procedures and 30 different descriptive statistics. ANOVA is comprehensive and includes general N factor analysis. Many unusual procedures are included e.g. survival analysis. All tests have associated information windows which give literature references and other facts to assist in getting the right one for the job. Probabilities are calculated directly so there is no need to use tables.

Stat-200 has a state-of-the-art user interface with all its statistical and plotting modules easily selected from the logical tree views. Procedures you use frequently can be placed in a Favorites list for instant access. The workbook is a powerful tool for manipulating and selecting data. It can be any size, limited only by your computer hardware. More than 65 data transforms are supplied and there is a high-level language built-in to enable any transform to be programmed by the user. Data can be keyed-in and also either copied and pasted or dragged and dropped from spreadsheets. In addition, spreadsheet files in many formats can be directly opened. Stat-200 is readily integrated with databases and it supports Recordset tables for ODBC database connections enabling data and results to be easily passed back and forth.

Graph types in Stat-200 include all the usual types for statistical data such as line, pie ,bar, scatter and box-whisker charts together with 3D plotting options. A wide variety of line graph styles is available including fits to polynomial, logarithmic, exponential and power functions and plots of moving averages, as well as graphs of raw data, means and data frequencies. In addition, many specialized graph types such as Kaplan-Meier, Weibull, Pareto, Shewart, Polar ect can be plotted automatically. Templates of frequently used graph styles can be created and saved.

Numeric results of tests can be printed direct from Stat-200 or copied to the clipboard or saved for import into other programs. Graphs can be printed or saved and saved and also exported as Windows Bitmaps or Windows Metafiles. Integration with the Web is enhanced by optional output of text in HTML and graphical results in JPG and PNG file formats.

Stat-200 Features

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

Nonparametric Tests

N×K Chi-squared
2×2 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 2×2 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-squqre test for k indeoendent samples
Kendall coefficient of agreement samples
Kappa statistic for nominally scaled data
Gamma statistic for orded variables
Lambda statistic for asymmetrical association
Somers d for asymmetrical associatio of ordered variables
Cox'sF-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 disperion test of two variances
Steel test for comparing K treatments with a control
Sequential test for a populatiob mean
Sequential test for a standard deviation
Adjacency test for randomness of fluctuations
Serial correlation test for randpmness of fluctuations
Turning point test for randomness of fluctuations
The difference sign test for randomness in a sample
Run-test on successive differences foe 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 equslity of multinomial distributions
Bowker test foe 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 randomizatiob test for interval -scale data
Pitman-Welch test for interval scale data
Wall test for nominal scale data
Pitman randomization test for inteval scale data
Angular-angular correlation
Watson U2 test（To test whether two samples from circular observations dffer significantly from each other, regarding mean direction or angular variance ）
Watson-Willams test（to test whether the mean angles of two independent circular observations differ significantly from each other）

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）
Minimun 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

Parametric Tests

Frequency analysis
Unpaired t-test

Paired t-test

Unequal variance test
Bonferroni t-test
One-way non-repeated ANOVA
One-way replicated ANOVA
Two-way replicated ANOVA
Two-way repeated ANOVA
Three-way ANOVA
Linear regression
Multiple linear regression
Compare two observed values
Compare 2 sample proportios
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 calssification ANCOVA for completely randomized design
Pearson R
Repeated measures linear regrassion
Backward elimination for multiple linear regression
Polynomial regression
Tigonometric regression
Linear-linear regression
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 of variance foe 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 correlated proportions
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）
Sign rank test for a mean
Sign 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 ragarding mean angle, angular variance or both）

Data Trabsforms

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
Absolte Value
Standardize
Center
Multiply columns
Divide columns
Add columns
Subtract columns
Error Function
Complementary error function
Logit
Probit
Normit
Normal probabilites
Student's 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

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）