Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning.
제공자:
Introduction to Statistics
스탠퍼드 대학교이 강좌에 대하여
- Basic familiarity with computers and productivity software
- No calculus required
- Basic familiarity with computers and productivity software
- No calculus required
제공자:

스탠퍼드 대학교
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
강의 계획표 - 이 강좌에서 배울 내용
Introduction and Descriptive Statistics for Exploring Data
This module provides an overview of the course and a review of the main tools used in descriptive statistics to visualize information.
Producing Data and Sampling
In this module, you will look at the main concepts for sampling and designing experiments. You will learn about curious pitfalls and how to evaluate the effectiveness of such experiments.
Probability
In this module, you will learn about the definition of probability and the essential rules of probability that you will need for solving both simple and complex challenges. You will also learn about examples of how simple rules of probability are used to create solutions for real-life complex situations.
Normal Approximation and Binomial Distribution
This module covers the empirical rule and normal approximation for data, a technique that is used in many statistical procedures. You will also learn about the binomial distribution and the basics of random variables.
Sampling Distributions and the Central Limit Theorem
In this module, you will learn about the Law of Large Numbers and the Central Limit Theorem. You will also learn how to differentiate between the different types of histograms present in statistical analysis.
Regression
This module covers regression, arguably the most important statistical technique based on its versatility to solve different types of statistical problems. You will learn about inference, regression, and how to do regression diagnostics.
검토
- 5 stars70.18%
- 4 stars20.29%
- 3 stars5.75%
- 2 stars2.14%
- 1 star1.62%
INTRODUCTION TO STATISTICS의 최상위 리뷰
All the basics you are going to need in one place. Lacks details however, and assumes you will fill in the blanks with your own reasearch and study.
A very good course. Definitely a course to take for an introduction into Statistics. Also probably going to be very useful as I'm planning on taking Machine Learning.
very good course to take , because this course was explained in detailed and also by doing the quiz of this course helpful to learn perfectly.
The course is extremely amazing! The presentation and materials are really easy to be understood. Thank you so much Professor and the team!
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
이 수료증을 구매하면 무엇을 이용할 수 있나요?
재정 지원을 받을 수 있나요?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.