# Master Statistics for Data Science and Business Analysis

Learn stats essentials for Data science

4.5/5

## Master Statistics for Data Science and Business Analysis

### What you’ll learn

Learn the foundational concepts of statistics
Learn the foundational concepts of measures of central tendency
Learn problems of statistics
Step by step solutions

### Requirements

Basic knowledge of Math will be needed to finish the course

### Description

In this course, we will learn statistics essentials for Data science and Business analysis. Since data science is studied by both the engineers and commerce students ,this course is designed in such a way that it is useful for both beginners as well as for advanced level. I am sure that this course will be create a strong platform for students and those who are planning for appearing in competitive tests and studying higher Mathematics .You will also get a good support in Q&A section . It is also planned that based on your feed back, new course materials like Importance of Statistics for Data Science, Statistical Data and its measurement scales, Classification of Data ,Measures of Dispersion: Range, Mean Deviation, Std. Deviation & Quartile Deviation, Basic Concepts of Probability, Sample Space and Verbal description & Equivalent Set Notations, Types of Events and Addition Theorem of Probability, Conditional Probability, Total Probability Theorem, Baye’s Theorem etc. will be added to the course. Hope the course will develop better understanding and boost the self confidence of the students.Waiting for you inside the course! So hurry up and Join now !!Important Note: The course is intended for purchase by adults. Those under 18 years may use the services only if a parent or guardian opens their account, handles any enrollments, and manages their account usage.

### Overview

Section 1: Introduction

Lecture 1 Measures of Central Tendency

Lecture 2 Q.no.1

Lecture 3 Q.no.2

Lecture 4 Q.no.3

Lecture 5 Q.no.4

Lecture 6 Q.no.1

Lecture 7 Q.no.2

Section 2: Combined and Weighted Arithmetic Means

Lecture 8 Combined Arithmetic Mean

Lecture 9 Illustrations to understand Combined Arithmetic Mean

Lecture 10 Weighted Arithmetic Mean

Lecture 11 Illustrations to understand Weighted Arithmetic Mean

Section 3: Measures of Dispersion

Lecture 12 Measures of Dispersion

Lecture 13 Illustrations (Range)

Lecture 14 Imporatant results on Standard Deviation

Section 4: Probability

Lecture 15 Introduction to Probability

Lecture 16 Illustrations to understand basic concepts of Probability

Section 5: Regression Analysis

Lecture 17 Introduction

Lecture 18 Illustration1

Lecture 19 Illustration2

Lecture 20 Illustration3

Lecture 21 Regression Coefficients and their Properties

Lecture 22 Illustration1

Lecture 23 Illustration2

Lecture 24 Important results about Regression Lines

Students of data science

#### Course Information:

Udemy | English | 2h 52m | 2.36 GB
Created by: Sandeep Kumar Mathur

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