What Does MVP Stand For? It’s Not What You Think.
October 7, 2024
Article
This course is part of Data Science Methods for Quality Improvement Specialization
Instructor: Wendy Martin
4,888 already enrolled
Included with
(32 reviews)
Recommended experience
Beginner level
Beginner level; no previous experience necessary.
(32 reviews)
Recommended experience
Beginner level
Beginner level; no previous experience necessary.
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
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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.
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.
7 videos3 readings2 assignments2 discussion prompts
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.
11 videos3 assignments2 discussion prompts
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.
8 videos2 assignments1 discussion prompt
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.
8 videos2 assignments1 discussion prompt
Upon completion of this module, students will be able to use R and RStudio to perform statistical tests for two groups with independent and dependent data.
13 videos2 assignments
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
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.
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University of Colorado Boulder
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University of Colorado Boulder
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University of Colorado Boulder
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This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
University of Colorado Boulder
Degree · 2 years
¹Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information.
32 reviews
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Reviewed on Aug 18, 2024
This is the course you can actually master the content in the course
Reviewed on Apr 18, 2021
We learned some theory and practiced in R. A perfect combination!
Reviewed on Mar 12, 2021
The instructor is clear and easy to follow. The lessons are succinct. It helps to be familiar with the topics already.
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