Understanding Statistical Models and Mathematical Models

سرفصل های دوره

This course covers important techniques from both mathematical and statistical modeling, including the use of ordinary differential equations to model deterministic systems, classic local search and simulated annealing to explore large search spaces.

1. Course Overview

1. Course Overview

2. Understanding Statistical and Mathematical Models

1. Version Check

2. Prerequisites and Course Outline

3. Understanding Mathematical Models and Statistical Models

4. Mathematical Models and Statistical Models - Differences and Applicati

5. Data and Metadata

6. Demo - Creating an Environment to Run the R Kernel on Jupyter Notebook

7. Demo - Associating Metadata Using the Comment Function

8. Demo - Querying and Setting Metadata Using the Meta Function

3. Case Studies on Statistical and Mathematical Models

1. Modeling Population Growth Using ODEs

2. Interpreting Derivatives

3. Verhulsts Decreasing Growth Model

4. Modeling Value at Risk - A Simplistic Model

5. Understanding Monte Carlo Simulations

6. Using Monte Carlo Simulations to Model Value at Risk

4. Applying Mathematical Models in R

1. Recap - Ordinary Differential Equations

2. Demo - Calculating the Derivative of a Function

3. Demo - Solving Differential Equations

4. Demo - Solving Verhulsts Equation for Population Growth

5. The 8 Queens Problem

6. Local Search Optimization Techniques

7. Demo - Setting up Helper Functions to Solve the 8 Queens Optimization Prob

8. Demo - Applying Local Search Optimization to Solve the Eight Queens Proble

5. Applying Statistical Models in R

1. Data Mining Statistics and Machine Learning

2. Understanding Hypothesis Testing

3. The T-test and the Z-test

4. Demo - Exploring the Automobile Dataset

5. Demo - One Sample T-test

6. Demo - One Sample Z-test

7. Demo - Two Sample T-test

8. Demo - Paired Sample T-test and Z-test

9. Summary and Further Study

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تولید کننده: PluralSight