Fergana politechnic institute faculty of mechanical engineering group of e18-21 student tulashev otabek higher mathematics presentation project


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FERGANA POLITECHNIC 
INSTITUTE 
FACULTY OF MECHANICAL 
ENGINEERING
GROUP OF E18-21 STUDENT 
TULASHEV OTABEK
HIGHER MATHEMATICS
PRESENTATION 
PROJECT
EXECUTED BY: TULASHEV
ACEPTED BY: SODIKKHUJAEVA SH
FERGANA 2022


TOPIC: EVALUATION OF 
INTERDEPENDENCE OF VARIABLES. 
VALUE OF THE REGRESSION 
EQUATION IN MULTIVARIATE 
REGRESSION
INTRODUCTION TO MULTIVARIATE 
REGRESSION
• IN TODAY'S WORLD, INFORMATION IS 
EVERYWHERE AND IT CAN BE DIFFERENT. 
DATA ANALYSIS IS THE APPLICATION OF 
STATISTICAL AND LOGICAL METHODS TO 
DESCRIBE AND VISUALIZE, REDUCE, REVISE, 
SUMMARIZE, AND EVALUATE DATA TO 
PROVIDE A BETTER CONTEXT FOR THAT 
DATA.
UNIVARIATE LINEAR REGRESSION
• SIMPLE LINEAR REGRESSION IS A 
REGRESSION MODEL THAT ESTIMATES THE 
RELATIONSHIP BETWEEN A DEPENDENT 
VARIABLE AND AN INDEPENDENT VARIABLE 
USING A STRAIGHT LINE.
Y = AX + B


MULTIVARIATE LINEAR REGRESSION
• MULTIVARIATE REGRESSION IS AN 
EXTENSION OF MULTIPLE REGRESSION 
WITH ONE DEPENDENT VARIABLE AND 
MULTIPLE INDEPENDENT VARIABLES. WE 
TRY TO PREDICT THE OUTPUT BASED ON 
THE NUMBER OF INDEPENDENT 
VARIABLES.
Y = AX+BZ+D OR Y =AX+BZ+…
REGRESSION ANALYSIS IS AN IMPORTANT 
STATISTICAL TECHNIQUE THAT ALLOWS 
YOU TO EXAMINE THE RELATIONSHIP 
BETWEEN TWO OR MORE VARIABLES IN A 
SET OF DATA.REGRESSION ANALYSIS 
ANSWERS THESE QUESTIONS:
• MA’LUMOTLARNING QAYSI BIRINI
E'TIBORSIZ QOLDIRISH MUMKIN? 
ULAR BIR-BIRI BILAN QANDAY
ALOQADA? 
• * BERILGAN MA’LUMOTLAR
QANCHALIK ISHONCHLI?


UNIVARIATE LINEAR REGRESSION
SIMPLE LINEAR REGRESSION IS A 
REGRESSION MODEL THAT ESTIMATES 
THE RELATIONSHIP BETWEEN A 
DEPENDENT VARIABLE AND AN 
INDEPENDENT VARIABLE USING A 
STRAIGHT LINE.
Y = AX + B

Document Outline

  • FERGANA POLITECHNIC INSTITUTE FACULTY OF MECHANICAL ENGINEERING GROUP OF E18-21 STUDENT TULASHEV OTABEK HIGHER MATHEMATICS PRESENTATION PROJECT Executed by: tulashev Acepted by: Sodikkhujaeva Sh
  • TOPIC: Evaluation of interdependence of variables. Value of the regression equation in multivariate regression
  • Слайд номер 3
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