1. Introduction of Predictive Modeling
2. Non Linear Regression
3. Anova and Control Charts
4. Understanding, Interpretation and implementation using Minitab
5. Continue on Interpretation and implementation using Minitab
6. Observation
7. Results for NAV Prices
8. NAV Prices - Observations
9. Descriptive Statistics
10. Customer Complaints-Observations
11. Resting Heart Rate Observations
12. Results for Loan Applicant MTW
13. More Details on Results for Loan Applicant MTW
14. Features of T- Test
15. Loan Applicant
16. Paired T - Test
17. Understanding and Implementation of ANOVA
18. Pairwise Comparisons
19. Features of Chi - Test
20. Preference and Pulse Rate
21. Diffe. btw Growth Plan ad Dividend Plan in MF
22. Checking NAV Price and Repurchase Price
23. Basic Correlation Techniques
24. More on Basic Correlation Techniques
25. CT Implementation Using Minitab
26. Continue on Implemetation using Minitab
27. Interpretation of Correlation Values
28. Results for Return
29. Correlation Values - Observations
30. Correlation Values - Interpretations
31. Heart Beat - Objective
32. Heart Beat - Interpretation
33. Demographics and Living Standards
34. Demographics and Living Standards - Observation
35. Graphical Implementation
36. Add Regression Fit
37. Scatterplot with Regression
38. Scatterplot of Rhdeq vs Rhcap
39. Introduction to Regression Modeling
40. Identify Independent Variable
41. Regression Equation
42. Tabulating the Values
43. Interpretation and Implementation on Data Sets
44. Continue on Interpretation on Database
45. Significant Variable
46. Calculating Corresponding Values
47. Identify Dependent Variable
48. Generate Descriptive Statistics
49. Scatterplot of Energy Consumption
50. Identity Equation
51. P - Value and T - Value
52. Changes in Tem. and Expansion
53. Objective of Stock Prices
54. Interpretations of Example 5
55. Reliance Return Change
56. Generate Predicted Values
57. Scatterplot Return RIL
58. Basic Multiple Regression
59. Basic Multiple Regression Continues
60. Basic Multiple Regression - Interpretation
61. Generate Basic Statistics
62. Working on Scatterplot
63. Dependent Variable Objective
64. Concept of Multicollinearity
65. Identify Dependent Variable Y
66. Outputs and Observation
67. Interpretations - Example 3
68. Calculate with and without Flux
69. Scatterplot of Heart FLux Vs Insolation
70. Interpretation of Datasets
71. Implementation of Datasets
72. Example 4 Observations
73. Display Descriptive Statistics
74. Predicted Values Example 4
75. Scatterplot of Example 4
76. Calculating IV - Multiple Regression
77. Calculating Independent Multiple Regression
78. Understanding Basic Logistic Scatter Plot
79. Basic Logistic Scatter Plot Continues
80. Generation of Regression Equation
81. Tabulated Values
82. Interpretation and Implementation on Dataset
83. Interpretation and Implementation on dataset Continues
84. Output and Observation - Tabulated Values
85. Business Metrics Example
86. Example Two and Three Interpretations
87. Regression Equation Group
88. Interpretation and Implementation of Scatter Plot
89. More on Implementation of Scatter Plot
90. Plastic Case Strength
91. Separate Equations
92. Generation of Predicted Values
93. Scatter Plot Strength Vs Temp
94. Data of Cereal Purchase
95. Children Viewed and RE
96. Predicted Values for Individual Customers
97. Income Independent Variable
98. Example of Credit Card Issuing
99. Example Five - Tabulated Values
100. Generating Outputs
101. Example Five Interpretations
102. Situations Income
103. Scatterplot
104. Scatter Plot Scale
105. Using Data Analysis Toolpak
106. Implementation of Descriptive Statistics
107. Descriptive statistics - Input Range
108. Implementation of ANOVA
109. Implementation of T - Test
110. Implementation Using Correlation
111. Implementation Using Regression
