655.52 MB | 00:20:27 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English

Files Included :
1 1 1 Course Introduction (17.02 MB)
2 1 2 Definition and Uses of Models Common Functions (34.36 MB)
3 1 3 How Models Are Used in Practice (32.94 MB)
4 1 4 Key Steps in the Modeling Process (19.15 MB)
5 1 5 A Vocabulary for Modeling (21.96 MB)
6 1 6 Mathematical Functions (40.93 MB)
7 1 7 Summary (17.4 MB)
1 2 1 Introduction to Linear Models and Optimization (40.1 MB)
2 2 2 Growth in Discrete Time (13.57 MB)
3 2 3 Constant Proportionate Growth (29.23 MB)
4 2 4 Present and Future Value (32.2 MB)
5 2 5 Optimization (27.48 MB)
6 2 6 Summary (15.83 MB)
1 3 1 Introduction to Probabilistic Models (28.12 MB)
10 3 10 The Normal Distribution (11.37 MB)
11 3 11 The Empirical Rule (17.62 MB)
12 3 12 Summary (8.6 MB)
2 3 2 Examples of Probabilistic Models (2.74 MB)
3 3 3 Regression Models (7.62 MB)
4 3 4 Probability Trees (8.21 MB)
5 3 5 Monte Carlo Simulations (13.05 MB)
6 3 6 Markov Chain Models (15.99 MB)
7 3 7 Building Blocks of Probability Models (15.7 MB)
8 3 8 The Bernoulli Distribution (12.38 MB)
9 3 9 The Binomial Distribution (33.19 MB)
1 4 1 Introduction to Regression Model (13.53 MB)
2 4 2 Use of Regression Models (34.79 MB)
3 4 3 Interpretation of Regression Coefficients (6.42 MB)
4 4 4 Rsquared and Root Mean Squared Error RMSE (27.22 MB)
5 4 5 Fitting Curves to Data (15.73 MB)
6 4 6 Multiple Regression (17.18 MB)
7 4 7 Logistic Regression (15.22 MB)
8 4 8 Summary of Regression Models (8.28 MB)