In this course, learners will be introduced to the field of statistics, including where data come from, study design, data management, and exploring and visualizing data. Learners will identify different types of data, and learn how to visualize, analyze, and interpret summaries for both univariate and multivariate data. Learners will also be introduced to the differences between probability and non-probability sampling from larger populations, the idea of how sample estimates vary, and how inferences can be made about larger populations based on probability sampling.
This course is part of the Statistics with Python Specialization
About this Course
High school algebra
What you will learn
Properly identify various data types and understand the different uses for each
Create data visualizations and numerical summaries with Python
Communicate statistical ideas clearly and concisely to a broad audience
Identify appropriate analytic techniques for probability and non-probability samples
Skills you will gain
- Data Analysis
- Python Programming
- Data Visualization (DataViz)
High school algebra
Syllabus - What you will learn from this course
WEEK 1 - INTRODUCTION TO DATA
WEEK 2 - UNIVARIATE DATA
WEEK 3 - MULTIVARIATE DATA
WEEK 4 - POPULATIONS AND SAMPLES
- 5 stars76.32%
- 4 stars18.35%
- 3 stars3.53%
- 2 stars0.89%
- 1 star0.89%
TOP REVIEWS FROM UNDERSTANDING AND VISUALIZING DATA WITH PYTHON
The course is very well structured. Teaching and links to related articles help us understand the concepts better. Jupyter notebook based python learning is very comfortable and easy to use.
This course is very good for the people who are not from programming background as everything related to the concepts is very well explained (with programming support) throughout the course
The course appearance may not as interesting as other courses, but if I have to name a course where my ability increases the most through the learning, I would choose this course. Thank you!
Really enjoyed this course. Looking forward to the next part of the specialization. I thought the quality of the lectures was excellent and made the topic interesting and digestible
About the Statistics with Python Specialization
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