Basic Statistics in Python (Correlations and T-tests)

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在此指导项目中,您将:

Clean data, including removing missing data and unnecessary columns

Explore data using descriptive statistics

Create visualizations of our data and analysis

Perform statistical tests, including t-tests and correlation

Clock1 hour 10 mins
Beginner初级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

By the end of this project, you will learn how to use Python for basic statistics (including t-tests and correlations). We will learn all the important steps of analysis, including loading, sorting and cleaning data. In this course, we will use exploratory data analysis to understand our data and plot boxplots to visualize the data. Boxplots also allow us to investigate any outliers in our datasets. We will then learn how to examine relationships between the different data using correlations and scatter plots. Finally, we will compare data using t-tests. Throughout this course we will analyse a dataset on Science and Technology from World Bank. The measures in this dataset are numeric, therefore you will learn how to handle and compare numeric data. This guided project is for anyone with an interest in performing statistical analysis using Python. This could be someone from a social science background with statistics knowledge who wants to advance their analysis, or anyone interested in analysing data.

您要培养的技能

  • Statistical Analysis
  • Data Cleansing
  • Summary Statistics
  • Pandas
  • Data Visualization (DataViz)

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Set up a new Google Colab notebook

  2. Load data into notebook

  3. Clean data to remove missing data and unnecessary columns

  4. Perform exploratory data analysis

  5. Create boxplots using for loops

  6. Explore relationships between data using correlation and scatter plots

  7. Perform t-tests to compare data from different years

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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