Selvamuthu D., Das D. Introduction to Statistical Methods, Design of Experiments and Statistical Quality Control

New York: Springer, 2018. — 442 p. — ISBN: 9789811317354, 9811317356.ForewordAcronyms
Statistics
Problem of Data Representation
Problem of Fitting the Distribution to the Data
Problem of Estimation of Parameters
Problem of Testing of Hypothesis
Problem of Correlation and Regression
History
Necessity
Applications
Statistical Quality ControlBasics of Probability
Definition of Probability
Conditional Probability
Total Probability Rule
Bayes' Theorem
Random Variable and Distribution Function
Discrete Type Random Variable
Continuous Type Random Variable
Function of a Random Variable
Mean
Variance
Moment of Order n
Generating Functions
Standard Probability Distributions
Standard Discrete and Continuous Distributions
The Normal Distribution
Central Limit TheoremData, Information, and Description
Types of Data
Frequency Tables
Graphical Representations of Data
Descriptive Measures
Central Tendency Measures
Variability Measures
Coefficient of Variation
Displaying the Measures and Preparing ReportsThe Chi-Square Distribution
Student's t-Distribution
F-Distribution
Some Important Results on Sampling Distributions
Order Statistics
Point Estimation
Definition of Point Estimators
Properties of Estimators
Method of Moments
Method of Maximum Likelihood
Asymptotic Distribution of MLEs
Confidence IntervalTesting of Statistical Hypothesis
Null and Alternate Hypothesis
Neyman–Pearson Theory
Likelihood Ratio Test
Test for the Population Mean
Test for the Variance
Test for the Distribution
Testing Regarding Contingency Tables
Test Regarding Proportions
Nonparametric Statistical Tests
Sign Test
Median Test
Kolmogorov Smirnov Test
Mann Whitney Wilcoxon U Test
Analysis of VarianceCorrelation
Causality
Rank Correlation
Multiple Correlation
Partial Correlation
Regression
Least Squares Method
Unbiased Estimator Method
Hypothesis Testing Regarding Regression Parameters
Confidence Interval for β
Regression to the Mean
Inferences Concerning the Mean Response of β + β x
Logistic RegressionCompletely Randomized Design
A Practical Problem
Data Visualization
Descriptive Model
Test of Hypothesis
Multiple Comparison Among Treatment Means (Tukey's Test)
Randomized Block Design
Data Visualization
Descriptive Model
Test of Hypothesis
Multiple Comparison Among Treatment Means
Latin Square Design
Descriptive Model
Test of Hypothesis
Multiple Comparison Among Treatment Means
Balanced Incomplete Block Design
Descriptive Model
Test of HypothesisA Practical Problem
Descriptive Model
Test of Hypothesis
Multiple Comparison Among Treatment Means
Descriptive Model
Test of Hypothesis
Display of Factorial Design
Analysis of Effects in Factorial Design
A Practical Problem
Regression Model
Response Surface
Display of Factorial Design
Analysis of Effects in Factorial Design
Yates' Algorithm
A Practical Example
Blocking and Confounding
Replicates as Blocks
Confounding
A Practical Example
Creation of - Factorial Design
Analysis of Effects in - Factorial Design with I=ABC
Analysis of Effects in - Factorial Design with I=-ABC
A Practical Example of - Factorial Design
A Practical Example of - Factorial Design
Design ResolutionResponse Surface Models
Multiple Linear Regression
Estimation of Coefficients: Least Square Method
Point Estimate of Coefficients
Hypothesis Test for Significance of Regression
Hypothesis Test on Individual Regression Coefficient
Interval Estimates of Regression Coefficients
Point Estimation of Mean
Adequacy of Regression Model
Analysis of First-Order Model
Location of Stationary Point
Nature of Stationary Point
Response Surface Designs
Experimental Designs for Fitting Second-Order Model
Multi-factor OptimizationAcceptance Sampling
Definition of a Single Sampling Plan
Operating Characteristic Curve
Rejectable Quality Level
Designing an Acceptance Sampling Plan
Effect of Sample Size on OC Curve
Double Sampling Plan for Attributes
Acceptance Sampling Plan
Designing of Acceptance Sampling Plan
Basis of Control Charts
Major Parts of a Control Chart
Statistical Basis for Choosing k Equal to
Analysis of Control Chart
The Mean Chart
The Range Chart
The Standard Deviation Chart (s-Chart)
Process Capability Analysis
Control Chart for Fraction Defectives
Control Chart for the Number of Defectives
Control Chart for The Number of Defects
CUSUM Control Chart
Exponentially Weighted Moving Average Control Chart
Construction of EWMA Control Chart
Choice of L and λStatistical Tables