Basic Statistics in Python (Correlations and T-tests)
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.
Status: Box Plots
Box Plots
Status: Data Cleansing
Data Cleansing
Beginner·Guided Project·2 hours
Featured reviews
5.0
·Reviewed Dec 3, 2020
This is a very helpful tool in research. Thank you very much!
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Nicholas
5.0
·Reviewed Feb 23, 2021
Great job with the project! Organized and well constructed, the challenges were great and the skills learned are DIRECTLY applicable to other projects I'm working on. Thanks! Looking forward to the next project with this instructor
M
Mauricio
3.0
·Reviewed Mar 30, 2021
After doing the course I realised there is a lot of emphasis on how to use the libraries to generate the different outcomes through out the course. However, the explanation of what to use and where, and the actual meaning of the values, comes a little too short.
A great learning experience, though.
A
Analyn
5.0
·Reviewed Dec 4, 2020
This is a very helpful tool in research. Thank you very much!
A
Aaliyah
5.0
·Reviewed Mar 5, 2024
Very good exercises.
M
Miguel
5.0
·Reviewed Aug 29, 2026
EXCELENTE
B
Bruno
4.0
·Reviewed Apr 14, 2025
Good course. It helped me a lot to write a project in data analysis. Even though the time proposed for this course was short, I would make things clearer reducing the pace - mainly towards the 2 last lessons when we explore correlation and t-tests.
M
Mohamad
3.0
·Reviewed Jan 2, 2022
A brief introduction into using data manipulation and statistical libraries in Python. It would have been helpful if the course explained the functions which were used: "lambda" for example. Among others, one of the main point stems from a final quiz question regarding "for loops". The question requires the student to select which option generates an error. Although the user is required to select one answer only, 3 out of the 4 options generate syntax errors due to missing closing parentheses, or colons.
M
Murad
3.0
·Reviewed Mar 21, 2021
too short
P
Parisa
2.0
·Reviewed May 17, 2023
The instructor's voice is too slow and sleepy. It makes it harder to follow along.