Managing, Describing, and Analyzing Data

4.4
stars
14 ratings

Wendy Martin

1,920 already enrolled

Offered By

Part of the Master of Science in Data Science degree

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Managing, Describing, and Analyzing Data

University of Colorado Boulder

About this Course

12,976 recent views

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 can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Beginner Level

Beginner level; no previous experience necessary.

Approx. 15 hours to complete

English

Subtitles: English

What 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 datadescribing datausing Rgraphing data

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Beginner Level

Beginner level; no previous experience necessary.

Approx. 15 hours to complete

English

Subtitles: English

Instructor

Instructor rating

4/5 (7 Ratings)

Wendy Martin

W. Edwards Deming Professor of Management

Engineering Management Program

1,920 Learners

1 Course

Offered by

University of Colorado Boulder

CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.

Start working towards your Master's degree

This course is part of the 100% online Master of Science in Data Science from University of Colorado Boulder. If you are admitted to the full program, your courses count towards your degree learning.

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Syllabus - What you will learn from this course

Week

Week 1

2 hours to complete

Data and Measurement

Upon completion of this module, students will be able to use R and R Studio to work with data and classify types of data using measurement scales.

2 hours to complete

7 videos (Total 48 min), 1 reading, 1 quiz

Week

Week 2

4 hours to complete

Describing Data Graphically and Numerically

Upon completion of this module, students will be able to use R and RStudio to create visual representations of data, and calculate descriptive statistics to describe location, spread and shape of data.

4 hours to complete

11 videos (Total 85 min)

11 videos

Create a Run Chart9m

Frequency Distributions7m

Frequency Polygons and Histograms7m

Histogram Patterns and Density Plots7m

Box and Whisker Plots7m

Measures of Central Tendency Mean9m

Measures of Central Tendency: Median, Mode7m

Measures of Position8m

Measures of Dispersion 7m

Measures of Shape6m

Measures of Relationship6m

2 practice exercises

Assessment: Describing Data Graphically1h 15m

Assessment: Describing Data Numerically1h 15m

Week

Week 3

3 hours to complete

Probability and Probability Distributions

Upon completion of this module, students will be able to apply the rules and conditions of probability and probability distributions to make decisions and solve problems using R and R Studio.

3 hours to complete

8 videos (Total 70 min)

Week

Week 4

3 hours to complete

Sampling Distributions, Error and Estimation

Upon completion of this module, students will be able to use R and RStudio to characterize sampling and sampling distributions, error and estimation with respect to statistical inference.

3 hours to complete

8 videos (Total 55 min)

Reviews

4.4

6 reviews

5 stars
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4 stars
21.42%
3 stars
7.14%
1 star
7.14%

TOP REVIEWS FROM MANAGING, DESCRIBING, AND ANALYZING DATA

by MWMar 12, 2021

The instructor is clear and easy to follow. The lessons are succinct. It helps to be familiar with the topics already.

by BTApr 18, 2021

We learned some theory and practiced in R. A perfect combination!

View all reviews

Frequently Asked Questions

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What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.

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Managing, Describing, and Analyzing Data

Managing, Describing, and Analyzing Data