Explore a comprehensive series of statistics screencasts designed for engineers, focusing on data analysis and regression techniques. Learn about various probability distributions, hypothesis testing, confidence intervals, and regression analysis methods. Master the use of tools like MATLAB, Excel, and POLYMATH for statistical computations and data visualization. Dive into advanced topics such as non-linear regression, ANOVA, and kinetics parameter determination. Gain practical skills through interactive simulations and real-world examples, including applications in chemical engineering and reactor kinetics. Enhance your ability to interpret statistical results, perform data-driven decision-making, and apply statistical methods to engineering problems.
Overview
Syllabus
Binomial Distribution.
Negative Binomial Distribution.
Geometric Distribution.
Hypergeometric Distribution.
Two Sample T-Test and Type-1 Error.
What Does a 95% Confidence Interval Mean? Part 1.
What Does a 95% Confidence Interval Mean? Part 2.
Creating a Scatter Plot using Regression Analysis.
Model Fitting and Regression in MATLAB.
Linear Regression: Meaning of p-Values for the Slope and Intercept.
Linear Regression: Meaning of Confidence Intervals for Slope and Intercept.
Regression Fitting in Excel-1.
Regression Fitting in Excel-2.
Multiple Regression in Excel.
Non-Linear Regression Introduction.
Non-Linear Regression/POLYMATH.
The Meaning of an F-Test.
Implementing an F-Test in MATLAB and Excel.
The Meaning of a One-Way ANOVA.
One-Way ANOVA in Excel.
Simple One-Way ANOVA in MATLAB.
The Meaning of a Two-Factor ANOVA.
Meaning of Student's t-Distribution (Simulation).
Calculating Confidence Intervals.
Histogram in Excel.
Simple Linear Regression (Simulation).
Aliasing - Sound (Interactive Simulation).
ANOVA Visualization (Interactive Simulation).
Nonlinear Transformations (Interactive Simulation).
Central Limit Theorem (Interactive Simulation).
Square Wave (Interactive Simulation).
P-Value From Test Statistic (Interactive Simulation).
Introduction to Nonlinear Regression.
Non-linear Regression for Kinetic Data.
Non-linear Regression for Kinetic Data Using POLYMATH.
Linear Regression for Kinetic Data.
Linear Regression for Kinetic Data Using POLYMATH.
Determining Michaelis-Menten Kinetics Parameters Using Nonlinear Regression.
Nonlinear Regression to Determine Michaelis-Menten Kinetics Parameters Using POLYMATH.
Nonlinear Regression to Determine Michaelis-Menten Kinetics Parameters Using Excel Solver.
Nonlinear Regression to Determine Confidence Limits for Michaelis-Menten Kinetics Parameters - Excel.
How to Determine Activation Energy Using Nonlinear Regression.
Determine Activation Energy Using Nonlinear Regression with POLYMATH.
Determine Activation Energy Using Nonlinear Regression with Excel Solver.
Calculate 95% Confidence Intervals for Nonlinear Regression in Excel Part 1.
Calculate 95% Confidence Intervals for Nonlinear Regression in Excel Part 2.
Determine Kinetic Parameters for Data from Isothermal Plug Flow Reactor Part 1: Overview.
Determine Kinetic Parameters for Data from Isothermal Plug Flow Reactors Part 2: Excel Calculations.
Determine Kinetic Parameters for Data from Isothermal Plug Flow Reactors Part 3: Excel Spreadsheet.
Determine Kinetic Parameters for Data from Isothermal Plug Flow Reactors Part 4: Confidence Limits.
Taught by
LearnChemE
