In this course, you will learn the basics of understanding the data you have and why correctly classifying data is the first step to making correct decisions. You will describe data both graphically and numerically using descriptive statistics and R software. You will learn four probability distributions commonly used in the analysis of data. You will analyze data sets using the appropriate probability distribution. Finally, you will learn the basics of sampling error, sampling distributions, and errors in decision-making.
This course is part of the Data Science Methods for Quality Improvement Specialization

About this Course
Beginner level; no previous experience necessary.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will learn
Calculate descriptive statistics and create graphical representations using R software
Solve problems and make decisions using probability distributions
Explore the basics of sampling and sampling distributions with respect to statistical inference
Classify types of data with scales of measurement
Skills you will gain
- analyzing data
- describing data
- using R
- graphing data
Beginner level; no previous experience necessary.
Could your company benefit from training employees on in-demand skills?
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Start working towards your Master's degree
Syllabus - What you will learn from this course
Data and Measurement
Describing Data Graphically and Numerically
Probability and Probability Distributions
Sampling Distributions, Error and Estimation
Reviews
- 5 stars65.21%
- 4 stars26.08%
- 3 stars4.34%
- 1 star4.34%
TOP REVIEWS FROM MANAGING, DESCRIBING, AND ANALYZING DATA
The instructor is clear and easy to follow. The lessons are succinct. It helps to be familiar with the topics already.
We learned some theory and practiced in R. A perfect combination!
About the Data Science Methods for Quality Improvement Specialization

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