Identical Populations Test

Identical Populations Test for Crosstable Data

Versión en Español
Colección de JavaScript Estadísticos en los E.E.U.U.
Sitio Espejo para América Latina

This site is a part of the JavaScript E-labs learning objects for decision making. Other JavaScript in this series are categorized under different areas of applications in the MENU section on this page.

Professor Hossein Arsham

For testing whether two or more random samples are drawn from the same population or from different populations. Construct the crosstable entering the data starting from the upper left corner without any gap, and then click the Calculate. Non-entry rows and columns are not included in the calculations.
In entering your data to move from cell to cell in the data-matrix use the Tab key not arrow or enter keys.
H₀: All the populations are almost identical. There are no significant distinctions among the populations.








Chisquare
P-value
Conclusion

For Technical Details, Back to:
Statistical Thinking for Decision Making

Kindly email your comments to:
Professor Hossein Arsham

Prueba de Poblaciones Idénticas para Datos de Tablas Cruzadas
Nota para los usuarios de habla hispana:
Para pruebas de dos o mas muestras aleatorias obtenidas de la misma o diferentes poblaciones. Construya la tabla cruzada introduciendo los datos comenzando desde el extremos superior izquierdo sin dejar espacios en blanco, y luego presione el botón Calculate (Calcular). Filas y columnas sin datos nos son incluidas en los cálculos.
Mientras entre sus datos en la matriz, muévase de celda a celda usando la tecla Tab, no use la flecha o la tecla de entrada
H₀: Totas la poblaciones son casi idénticas. No existen distinciones suficientes entre las poblaciones.
Los resultados que usted obtendrá son:
Chisquare = Chi cuadrado
P –Value = Valor P
Conclusion = Conclusión:
Very strong evidence against the null hypothesis = Evidencia bastante fuerte en contra de la hipótesis nula
Moderate evidence against the null hypothesis = Evidencia moderada en contra de la hipótesis nula
Suggestive evidence against the null hypothesis = Evidencia subjetiva en contra de la hipótesis nula
Little or no real evidences against the null hypothesis = Poca o no evidencia real en contra de la hipótesis nula
Strong evidence against the null hypothesis = Evidencia fuerte en contra de la hipótesis nula
Para Detalles Técnicos y Aplicaciones, Vuelta a:
Razonamiento Estadístico para la Toma de Decisiones Gerenciales

MENU

Decision Tools in Economics & Finance

ABC Inventory Classification
Autoregressive Time Series
Beta and Covariance Computations
Bivariate Discrete Distributions
Break-Even Analysis and Forecasting
Categorized Probabilistic, and Statistical Tools
Detecting Trend & Autocrrelation
Determination of the Outliers
Forecasting by Smoothing
Inventory Control Models
Linear Optimization Solvers to Download
Linear Optimization with Sensitivity
Maths of Money: Compound Interest Analysis
Matrix Algebra, and Markov Chains
Mean, and Variance Estimations
Measuring Forecast Accuracy
Other Polynomial Regressions
Optimal Age for Replacement
Parametric System of Linear Equations
Performance Measures for Portfolios
Plot of a Time Series
Predictions by Regression
Proportion Estimation
Quadratic Regression
Regression Modeling
Seasonal Index
Single-period Inventory Analysis
Summarize Your Data
System of Equations, and Matrix Inversion
Test for Random Fluctuations
Test for Seasonality
Test for Stationary Time Series
Time Series' Statistics

Probabilistic Modeling

Bayesian Inference for the Mean
Bayes' Revised Probability
Bivariate Discrete Distributions
Comparing Two Random Variables
Decision Making Under Uncertainty
Determination of Utility Function
Making Risky Decisions
Measure the Quality of Your Decision
Multinomial Distributions
Two-Person Zero-Sum Games

Statistics

Analysis of Covariance
ANOVA for Condensed Data Sets
ANOVA for Dependent Populations
ANOVA: Testing the Means
Bayesian Statistical Inference
Bivariate Sampling Statistics
Chi-square Test for Relationship
Compatibility of Multi-Counts
Confidence Intervals for Two Populations
Descriptive Statistics
Determination of the Outliers
Empirical Distribution Function
Equality of Multi-variances
Estimations With Confidence
Goodness-of-Fit for Discrete Variables
Identical Populations Testing
Index Numbers with Applications
K-S Test for Equality of Two Populations
Lilliefors Test for Exponentially
Multiple Regressions
Percentage: Estimation & Testing
Paired Proportion Test
Polynomial Regressions
Pooling Means, and Variances
P-values for the Popular Distributions
Quadratic Regression
Sample Size Determination
Revising the Mean and the Variance
Scattered Diagram and the Outliers
Simple Linear Regression
Subjective Assessment of Estimates
Subjectivity in Hypothesis Testing
Test for Several Correlation Coefficients
Test for Homogeneity of a Population
Test for Normality
Test for Uniform Distribution
Testing Poisson Process
Test for Randomness
Testing Several Proportions
Testing the Mean
Testing the Medians
Testing the Correlation Coefficient
Testing Two Populations
Testing the Variance
The Before-and-After Test
The Other Means
Two-Way ANOVA Test
Two-Way ANOVA with Replications

The Copyright Statement: The fair use, according to the 1996 Fair Use Guidelines for Educational Multimedia, of materials presented on this Web site is permitted for non-commercial and classroom purposes only.
This site may be translated and/or mirrored intact (including these notices), on any server with public access. All files are available at http://home.ubalt.edu/ntsbarsh/Business-stat for mirroring.
Kindly e-mail me your comments, suggestions, and concerns. Thank you.
Professor Hossein Arsham

Back to:
Dr Arsham's Home Page