Statistics Fundamentals (1/9) Introduction
Basic Statistics for Data Science
Development,Data Science and AI ML,Data Analysis
Lectures -8
Duration -34 mins
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Course Description
Welcome to Statistics Fundamentals! This course is for beginners who are interested in statistical analysis. And anyone who is not a beginner but wants to go over from the basics is also welcome!
Statistical Analysis is now applied in various scientific and practical fields. As a science field, statistics is a discipline that concerns collecting data, and mathematical analysis of the collected data, describing data and making inference from the data. Using statistical methods, we can obtain insights from data, and use the insights for answering various questions and decision making.
To obtain meaningful insights from data, we need to learn statistics both in practical and theoretical viewpoints. This course intends to provide you with theoretical knowledge as well as Python coding. Theoretical knowledge enables us to implement appropriate analysis in various situations. And it can be a useful foundation for more advanced learning.
This course is the first chapter of Statistics Fundamentals, a comprehensive program for learning the basics of statistics. This series will consist of the following 9 courses, including this one.
1. Introduction ( This course!)
2. Descriptive Statistics
3. Probability
4. Probability Distribution
5. Sampling
6. Estimation
7. Hypothesis Testing
8. Correlation & Regression
9. ANOVA
This introduction course does not contain coding lectures, but other courses in this program have Python tutorial lectures. They cover basic Python coding, so if you do not have Python coding experience, I believe they are easy to follow for you. But this program is not a Python course, so learners who have not installed Python and related tools, please use other references.
This course is an introductory course in Statistics Fundamentals and covers the following topics.
1. What is Statistics?
2. Type of Statistics
3. What is Data?
4. Stevens' Typology
5. Independent and Dependent Variables
Goals
- Definition of Statistics
- Types of Statistics
- Data Typoplogy
Prerequisites
- None
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
7 Lectures
-
What is Statistics? 08:03 08:03
-
Types of Statistics 05:52 05:52
-
What is Data? 06:42 06:42
-
Stevens' Typology 06:01 06:01
-
How to Distinguish? 04:55 04:55
-
Independent & Dependent Variables 01:56 01:56
-
Thank you! 00:32 00:32
Instructor Details
![Takuma Kimura](https://www.tutorialspoint.com/assets/profiles/331697/profile/200_32114-1619024542.jpg)
Takuma Kimura
Profile Summary:
Dr. Takuma Kimura is an internationally recognized scholar in business and management fields. His expertise includes research in organizational behavior, and practical business analytics in human resource management and marketing. He teaches these subjects in universities and industrial companies.
Professional Details:
He published more than 10 academic papers in internationally prominent journals such as Journal of Business Ethics, International Journal of Management Reviews, Industrial Marketing Management.
He is awarded as one of the World Top Reviewers from Publons, and as a Recognized Reviewer from European Management Journal.
He is technically skilled for Statistical Analysis, Machine Learning, Data Science, Qualitative Analysis. And he has abundant knowledge in management theory, especially in organizational behavior and psychology.
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