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Estimated Time
35 hours
Enroll by
February 2, 2022
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Prerequisites
Python & SQL
In collaboration with
What You Will Learn
Syllabus
Practical Statistics
Prerequisite Knowledge
Python & SQL.
Simpson’s Paradox
Examine a case study to learn about Simpson’s Paradox.
Binomial Distribution
Learn about binomial distribution where each observation represents one of two outcomes and derive the probability of a binomial distribution.
Bayes Rule
Build on conditional probability principles to understand the Bayes rule and derive the Bayes theorem.
Sampling Distributions and Central Limit Theorem
Use normal distributions to compute probabilities and the Z-table to look up the proportions of observations above, below or in between values.
Hypothesis Testing
Use critical values to make decisions on whether or not a treatment has changed the value of a population parameter.
T-Tests and A/B Tests
Test the effect of a treatment or compare the difference in means for two groups when we have small sample sizes.
Logistic Regression
Use logistic regression results to make a prediction about the relationship between categorical dependent variables and predictors.
Course Project: Analyze A/B Test Results
In this project, you will be provided a dataset reflecting data collected from an experiment. You’ll use statistical techniques to answer questions about the data and report your conclusions and recommendations in a report.
59%
of companies plan to increase positions requiring data analysis skills.
Introducing new Udacity Single Courses
Introducing new Udacity Single Courses
Our students asked and we listened. You can now get the in-demand tech skills you need faster and for less money by enrolling in one of our new, one-month Single Courses. You’ll get the specific job-ready skills you need in as little as four weeks and for a fraction of the cost.
Of course if you are looking for a more robust, in-depth education, you can still enroll in one of our 3-6 month Nanodegree programs.
Both programs are part-time and online, and they both offer 24/7 support, quality Udacity-produced content, courses created with the help of top tech companies, and more. You can always start with a Single Course and upgrade to a full Nanodegree program if you like.
Of course if you are looking for a more robust, in-depth education, you can still enroll in one of our 3-6 month Nanodegree programs.
Both programs are part-time and online, and they both offer 24/7 support, quality Udacity-produced content, courses created with the help of top tech companies, and more. You can always start with a Single Course and upgrade to a full Nanodegree program if you like.
Course OfferingsFull list of offerings included:
Enrollment Includes:
Class Content
Real-world projects
Project reviews
Project feedback from experienced reviewers
Student Services
Technical mentor support
New
Student community
Improved
Succeed with Personalized Services
We provide services customized for your needs at every step of your learning journey to ensure your success!
Get timely feedback on your projects
Reviews By the numbers
1,400+ project reviewers
2.7M projects reviewed
88/100 reviewer rating
1.1 hours avg project review turnaround time
Reviewer Services
- Personalized feedback
- Unlimited submissions and feedback loops
- Practical tips and industry best practices
- Additional suggested resources to improve
Mentors available to answer your questions
Mentors by the numbers
1,400+ technical mentors
0.85 hours median response time
Mentorship Services
- Support for all your technical questions
- Questions answered quickly by our team of technical mentors
Learn with the best
Josh Bernhard
Data Scientist at Nerd Wallet
Josh has been sharing his passion for data for nearly a decade at all levels of university, and as Lead Data Science Instructor at Galvanize. He's used data science for work ranging from cancer research to process automation.
Sebastian Thrun
Instructor
As the founder and president of Udacity, Sebastian’s mission is to democratize education. He is also the founder of Google X, where he led projects including the Self-Driving Car, Google Glass, and more.
Derek Steer
CEO at Mode
Derek is the CEO of Mode Analytics. He developed an analytical foundation at Facebook and Yammer and is passionate about sharing it with future analysts. He authored SQL School and is a mentor at Insight Data Science.
Juno Lee
Curriculum Lead at Udacity
Juno is the curriculum lead for the School of Data Science. She has been sharing her passion for data and teaching, building several courses at Udacity. As a data scientist, she built recommendation engines, computer vision and NLP models, and tools to analyze user behavior.
Mike Yi
Data Analyst Instructor
Mike is a content developer with a multidisciplinary academic background, including math, statistics, physics, and psychology. Previously, he worked on Udacity's Data Analyst Nanodegree program as a support lead.
David Venturi
Data Analyst Instructor
Formerly a chemical engineer and data analyst, David created a personalized data science master's program using online resources. He has studied hundreds of online courses and is excited to bring the best to Udacity students.
Sam Nelson
Product Lead
Sam is the Product Lead for Udacity’s Data Analyst, Business Analyst, and Data Foundations programs. He’s worked as an analytics consultant on projects in several industries, and is passionate about helping others improve their data skills.
Practical Statistics
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Learn
Key concepts and techniques of inferential statistics. Use them to tackle real-world challenges, such as analyzing AB tests and building regression models.
Average Time
On average, successful students take 35 hours to complete this program.
Benefits include
- Real-world projects from industry experts
- Technical mentor support
Program Details
Do I need to apply? What are the admission criteria?
No. This Course accepts all applicants regardless of experience and specific background.What are the prerequisites for enrollment?
In order to succeed in this program, we recommend having experience working with SQL and with data in Python, ideally with the NumPy and/or pandas libraries.How is this course structured?
The Practical Statistics course is comprised of content and curriculum to support one project. We estimate that students can complete the program in 35 hours.
The project will be reviewed by the Udacity reviewer network and platform. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.How long is this course?
Access to this course runs for the length of time specified in the payment card above. If you do not graduate within that time period, you will continue learning with month to month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our programs.Can I switch my start date? Can I get a refund?
Please see the Udacity Program Terms of Use and FAQs for policies on enrollment in our programs.What software and versions will I need in this course?
You will need access to the Internet, and a 64 bit computer. Additional software such as Python and its common data analysis libraries (e.g., Numpy and Pandas) will be required, but the program will guide students on how to download once the course has begun.