NMath Stats User's Guide

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Contents

Chapter 1. Introduction

1.1 Product Features

1.2 Software Requirements

1.3 Namespaces

1.4 Building and Deploying NMath Stats Applications

1.5 Documentation

1.6 Visualization

1.7 Technical Support

Chapter 2. Data Frames

2.1 Column Types

2.2 Creating DataFrames

2.3 Adding and Removing Columns

2.4 Adding and Removing Rows

2.5 Properties of DataFrames

2.6 Accessing DataFrames

2.7 Subsets

2.8 Accessing Sub-Frames

2.9 Reordering DataFrames

2.10 Factors

2.11 Cross-Tabulation

2.12 Exporting Data from DataFrames

Chapter 3. Descriptive Statistics

3.1 Column Types

3.2 Missing Values

3.3 Counts and Sums

3.4 Min/Max Functions

3.5 Ranks, Percentiles, Deciles, and Quartiles

3.6 Central Tendency

3.7 Spread

3.8 Shape

3.9 Covariance, Correlation, and Autocorrelation

3.10 Sorting

3.11 Logical Functions

Chapter 4. Special Functions

4.1 Combinatorial Functions

4.2 Gamma Function

4.3 Beta Function

Chapter 5. Probability Distributions

5.1 Distribution Classes

5.2 Correlated Random Inputs

5.3 Box-Cox Power Transformations

Chapter 6. Hypothesis Tests

6.1 Common Interface

6.2 One Sample Z-Test

6.3 One Sample T-Test

6.4 Two Sample Paired T-Test

6.5 Two Sample Unpaired T-Test

6.6 Two Sample F-Test

6.7 Pearson's Chi-Square Test

6.8 Fisher's Exact Test

Chapter 7. Linear Regression

7.1 Creating Linear Regressions

7.2 Regression Results

7.3 Predictions

7.4 Accessing and Modifying the Model

7.5 Significance of Parameters

7.6 Significance of the Overall Model

Chapter 8. Logistic Regression

8.1 Regression Calculators

8.2 Creating Logistic Regressions

8.3 Check for Convergence

8.4 Goodness of Fit

8.5 Parameter Estimates

8.6 Predicted Probabilities

Chapter 9. Analysis of Variance

9.1 One-Way ANOVA

9.2 One-Way Repeated Measures ANOVA

9.3 Two-Way ANOVA

9.4 Two-Way Repeated Measures ANOVA

Chapter 10. Non-Parametric Tests

10.1 One Sample Kolmogorov-Smirnov Test

10.2 Two Sample Kolmogorov-Smirnov Test

10.3 Shapiro-Wilk Test

10.4 One Sample Anderson-Darling Test

10.5 Kruskal-Wallis Test

Chapter 11. Multivariate Techniques

11.1 Principal Component Analysis

11.2 Factor Analysis

11.3 Hierarchical Cluster Analysis

11.4 K-Means Clustering

Chapter 12. Nonnegative Matrix Factorization

12.1 Nonnegative Matrix Factorization

12.2 Data Clustering Using NMF

Chapter 13. Partial Least Squares

13.1 Computing a PLS Regression

13.2 Error Checking

13.3 Predicted Values

13.4 Analysis of Variance

13.5 PLS Algorithms

13.6 Cross Validation

Chapter 14. Goodness of Fit

14.1 Significance of the Overall Model

14.2 Significance of Parameters

Chapter 15. Process Control

15.1 Process Capability

15.2 Process Performance

15.3 Z Bench

Index


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