Statistics for Experimentalists

IIT Madras Course , Prof. A. Kannan

114 students enrolled

Overview

Introduction and overview - Random Variables - Discrete Probability Distributions - Example Problems - Continuous Probability Distributions - Normal and Log Normal Probability Distributions - t-distribution - Chi-Square Distribution - F-distribution - Example Problems - Example Problems - Distribution of the random sample mean - Central Limit Theorem and its applications - Confidence Intervals - Maximum Likelihood Parameter Estimation - Example Problems - Formulation and Testing of Hypotheses - Errors in Hypothesis Testing - Hypothesis tests on population means, variances and ratio of variances

Design and Analysis of Single Factor Experiments - Randomized Block Design - Example Problems - Factorial Design with Two Factors - Factorial Design with Multiple Factors - Fractional Factorial Design - Example Problems - Matrix Approach to Linear Regression Analysis - Variance-Covariance Matrix - ANOVA in regression Analysis and Confidence Intervals - Extra Sum of Squares - Lack of Fit Analysis - Example Problems - Properties of Orthogonal Designs - Importance of Center Runs - Central Composite Design - Box Behnken Design and Face Centered Designs - Response Surface Methodology : Method of Steepest Ascent - Identification of optimal process conditions

Lecture 1: Introduction

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        Lecture Details

        Statistics for Experimentalists by Dr. A. Kannan,Department of Chemical Engineering,IIT Madras.For more details on NPTEL visit httpnptel.ac.in

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