Data Science for Business and Decision Making

<p>Part 1: Foundations of Business Data Analysis<br>1. Introduction to Data Analysis and Decision Making<br>2. Type of Variables and Mensuration Scales</p> <p>Part 2: Descriptive Statistics<br>3. Univariate Descriptive Statistics<br>4. Bivariate Descriptive Statistics</p> <p>Part 3: Probabilistic Statistics<br>5. Introduction of Probability<br>6. Random Variables and Probability Distributions</p> <p>Part 4: Statistical Inference<br>7. Sampling<br>8. Estimation<br>9. Hypothesis Tests<br>10. Non-parametric Tests</p> <p>Part 5: Multivariate Exploratory Data Analysis<br>11. Cluster Analysis<br>12. Principal Components Analysis and Factorial Analysis</p> <p>Part 6: Generalized Linear Models<br>13. Simple and Multiple Regression Models<br>14. Binary and Multinomial Logistics Regression Models<br>15. Regression Models for Count Data: Poisson and Negative Binomial</p> <p>Part 7: Optimization Models and Simulation<br>16. Introduction to Optimization Models: Business Problems Formulations and Modeling<br>17. Solution of Linear Programming Problems<br>18. Network Programming<br>19. Integer Programming<br>20. Simulation and Risk Analysis</p> <p>Part 8: Other Topics <br>21. Design and Experimental Analysis <br>22. Statistical Process Control <br>23. Data Mining and Multilevel Modeling<br></p>