수천 개 기업의 학습자들이 사랑하는
2명 이상을 교육하시나요?
DataCamp for Business 체험강의 설명
선수 조건
Python Toolbox1
Graphical Exploratory Data Analysis
Before diving into sophisticated statistical inference techniques, you should first explore your data by plotting them and computing simple summary statistics. This process, called exploratory data analysis, is a crucial first step in statistical analysis of data.
2
Quantitative Exploratory Data Analysis
In this chapter, you will compute useful summary statistics, which serve to concisely describe salient features of a dataset with a few numbers.
3
Thinking Probabilistically-- Discrete Variables
Statistical inference rests upon probability. Because we can very rarely say anything meaningful with absolute certainty from data, we use probabilistic language to make quantitative statements about data. In this chapter, you will learn how to think probabilistically about discrete quantities: those that can only take certain values, like integers.
4
Thinking Probabilistically-- Continuous Variables
It’s time to move onto continuous variables, such as those that can take on any fractional value. Many of the principles are the same, but there are some subtleties. At the end of this final chapter, you will be speaking the probabilistic language you need to launch into the inference techniques covered in the sequel to this course.
Python으로 하는 Statistical Thinking (파트 1)
강의 완료
DataCamp for Mobile을 통해 데이터 분석 능력을 향상시키세요.
모바일 강좌와 매일 5분 코딩 챌린지를 통해 이동 중에도 학습 효과를 높이세요.