Back to Basic Statistics in Python (Correlations and T-tests)

## Learner Reviews & Feedback for Basic Statistics in Python (Correlations and T-tests) by Coursera Project Network

4.4
stars
30 ratings

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....

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## 1 - 7 of 7 Reviews for Basic Statistics in Python (Correlations and T-tests)

By Nicholas S

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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

By Mauricio C

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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.

By Analyn B

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Dec 4, 2020

This is a very helpful tool in research. Thank you very much!

By Aaliyah R

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Mar 5, 2024

Very good exercises.

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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.

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Mar 21, 2021

too short

By Parisa T

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May 17, 2023

The instructor's voice is too slow and sleepy. It makes it harder to follow along.