Coursera 笔记

IBM

Statistics for Data Science with Python

数据科学统计（Python）

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Module 01

Course Introduction and Python Basics

5 篇
  1. 01Welcome from your Instructors!讲师寄语
  2. 02Course Overview课程概述
  3. 03Python Packages for Data SciencePython 数据分析库
  4. 04(Optional) Basics of Jupyter Notebooks（可选）Jupyter Notebook 基础
  5. 05(Optional) Python Review（可选）Python 复习
Module 02

Introduction & Descriptive Statistics

7 篇
  1. 01Welcome to Statistics!统计学入门
  2. 02Types of Data数据类型
  3. 03Measure of Central Tendency集中趋势度量
  4. 04Measure of Dispersion离散程度度量
  5. 05Lab: Descriptive Statistics实验：描述性统计
  6. 06Practice Quiz - Introduction to Descriptive Statistics练习测验：描述性统计入门
  7. 07Introduction and Descriptive Statistics绪论与描述性统计
Module 03

Data Visualization

6 篇
  1. 01Visualization Fundamentals可视化基础
  2. 02Statistics by Groups分组统计
  3. 03Statistical Charts统计图表
  4. 04Introducing the teacher's rating data教学评价数据简介
  5. 05Lab: Visualizing Data实验：数据可视化
  6. 06Practice Quiz - Data Visualization练习测验：数据可视化
Module 04

Introduction to Probability Distributions

0 / 7 篇
  1. 01Random Numbers and Probability Distributions
  2. 02State your hypothesis
  3. 03Alpha (α) and P-value
  4. 04Normal Distribution
  5. 05T distribution
  6. 06Probability of Getting a High or Low Teaching Evaluation
  7. 07Standard Normal Table
Module 05

Hypothesis testing

0 / 5 篇
  1. 01z-test or t-test
  2. 02Dealing with tails and rejections
  3. 03Equal vs unequal variances
  4. 04ANOVA
  5. 05Correlation tests
Module 06

Regression Analysis

0 / 4 篇
  1. 01Regression - the workhorse of statistical analysis
  2. 02Regression in place of t - test
  3. 03Regression in place of ANOVA
  4. 04Regression in place of Correlation
Module 07

Project Case: Boston Housing Data

0 / 2 篇
  1. 01Project Case Scenario
  2. 02Reading: Final Project Submission Guidelines and Deliverables
Module 09

Other Resources

0 / 2 篇
  1. 01Cheat sheet for Statistical Analysis in Python
  2. 02IBM Digital Badge