preface
prolog
-Welcome to Norn.

Chapter 1 Basic Knowledge
1.
Rules of notation
2.
Inverse function
3.
Exponential and natural logarithmic functions
4.
Properties of exponential and logarithmic functions
5.
differential
6.
procession
7.
Quantitative data and categorical data
8.
Sum of squared deviations and variance/standard deviation
9.
probability density function

Chapter 2 Regression Analysis
1.
What is regression analysis?
2.
Example of regression analysis
3.
Notes on the 'Order of Regression Analysis'
4.
Standardized residuals
5.
Interpolation and extrapolation
6.
Series correlation
7.
Regression equation other than a straight line

Chapter 3 Multiple Regression Analysis
1.
What is multiple regression analysis?
2.
Example of multiple regression analysis
3.
Notes on the 'Order of Multiple Regression Analysis'
4.
Standardized residuals
5.
Confidence and prediction intervals in Mahalanobis's distance and multiple regression analysis
6.
Multiple regression analysis when independent variables have unmeasurable data
7.
multicollinearity
8.
'The influence of each independent variable on the dependent variable' and multiple regression analysis

Chapter 4 Logistic Regression Analysis
1.
What is logistic regression analysis?
2.
Best method
3.
Method of selecting dependent variables
4.
Example of logistic regression analysis
5.
Notes on the 'Order of Logistic Regression Analysis'
6.
Ozby
7.
The name 'black'
8.
Bubble chart

Appendix Let's calculate it with Excel!
1.
base of natural logarithm
2.
exponential function
3.
natural logarithm function
4.
Matrix multiplication
5.
Inverse matrix
6.
Scale of the horizontal axis of the chi-square distribution
7.
Probability of chi-square distribution
8.
Scale of the horizontal axis of the F distribution
9.
Probability of F distribution
10.
(Partial) regression coefficient of (middle) regression equation
11.
Regression coefficients of logistic regression

References
Search

1.
Learn more easily and more accurately!
The more difficult the problem, the more you need to start from the basics.
This book uses comics to explain essential information to readers in a fun way.
In addition, we have thoroughly covered the basic concepts to help you understand what regression analysis is.

2.
Ask and answer questions with Q&A!
No matter how easily a theory is explained, there are always things to be curious about.
To this end, we have used the main characters of the cartoon to point out parts that readers may be curious about and separately summarized the parts that readers must know so that they can easily remember them.


3.
Detailed calculation process!!
This book describes the calculation process in detail, so readers with some mathematical knowledge can easily understand it, and even readers who are not good at mathematics can grasp the general flow just by skimming it.