Section 1: Basic Regression Modelling
1 Introduction to Regression Modeling
2 Identify Independent Variable
3 Regression Equation
4 Tabulating the Values
Section 2: Interpretation and Implementation on Data sets
5 Interpretation and Implementation on Data Sets
6 Continue on Interpretation on Database
7 Significant Variable
8 Calculating Corresponding Values
9 Identify Dependent Variable
10 Generate Descriptive Statistics
11 Scatterplot of Energy Consumption
12 Identity Equation
13 P – Value and T – Value
14 Changes in Tem. and Expansion
15 Objective of Stock Prices
16 Interpretations of Example 5
17 Reliance Return Change
18 Generate Predicted Values
19 Scatterplot Return RIL
20 Calculating IV – Linear Regression
21 Calculating Linear Regression Continues
Section 3: Basic Multiple Regression Interpretation and implementation on Data Sets
22 Basic Multiple Regression
23 Basic Multiple Regression Continues
24 Basic Multiple Regression – Interpretation
25 Generate Basic Statistics
26 Working on Scatterplot
27 Working on Scatterplot
28 Dependent Variable Objective
29 Concept of Multicollinearity
30 Identify Dependent Variable Y
31 Outputs and Observation
32 Interpretations – Example 3
33 Calculate with and without Flux
34 Scatterplot of Heart FLux Vs Insolation
35 Interpretation of Datasets
36 Implementation of Datasets
37 Example 4 Observations
38 Display Descriptive Statistics
39 Predicted Values Example 4
40 Scatterplot of Example 4
41 Calculating IV – Multiple Regression
42 Calculating Independent Multiple Regression
43 Understanding Basic Logistic Scatter Plot
44 Basic Logistic Scatter Plot Continues
45 Generation of Regression Equation
46 Tabulated Values
47 Interpretation and Implementation on Dataset
48 Interpretation and Implementation on dataset Continues
49 Output and Observation – Tabulated Values
50 Business Metrics Example
51 Example Two and Three Interpretations
52 Regression Equation Group
53 Interpretation and Implementation of Scatter Plot
54 More on Implementation of Scatter Plot
55 Plastic Case Strength
56 Separate Equations
57 Generation of Predicted Values
58 Scatter Plot Strength Vs Temp
59 Data of Cereal Purchase
60 Children Viewed and RE
61 Predicted Values for Individual Customers
62 Income Independent Variable
63 Example of Credit Card Issuing
64 Example Five – Tabulated Values
65 Generating Outputs
66 Example Five Interpretations
67 Situations Income
68 Adding Predicted Values
69 Scatter Plot Scale
