Brief Introduction
Analyze data using statistical methods and technology.
Description
This course helps prepare you for positions that require the analysis of large data sets, providing the statistics foundation you’ll need for data analysis.
You’ll learn how to model real-world applications using statistical methods. You’ll also gain skills to set up those applications in statistical frameworks, solve the statistical problems using technology and apply those results to answer real business questions. By leveraging the pandas and matplotlib python libraries, you’ll gain exposure to tools used in data analysis, visualization, and data science.
This course specifically explores inferential statistics - the science of applying statistical techniques to quantify and answer real-world data analysis questions.
The content covers three components – descriptive statistics and probability, hypothesis tests and confidence intervals and linear regression analysis.
Upon completing this course, you’ll be able to:
Formulate real-world data analysis questions as problems in statistical frameworks
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Explain how statistical concepts are applied in authentic situations
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Represent data numerically and visually
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Calculate and apply general and normal distribution probabilities
Analyze real-world problems using hypothesis tests and confidence interval techniques
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Construct hypothesis test and confidence interval models to solve problems
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Calculate hypothesis test and confidence interval results using technology
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Interpret the results of hypothesis test and confidence interval calculations
Analyze real-world problems using linear regression analysis techniques
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Construct linear regression models to solve problems
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Calculate linear regression results using technology
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Interpret the results of linear regression calculations
This is the second course in the introductory, undergraduate-level offering that makes up the larger Business Analytics Foundations MicroBachelors program. We recommend taking them in order, unless you have a background in these areas already and feel comfortable skipping ahead.
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Scripting with Python - starting February 2021
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Applied Statistics with Python - starting February 2021
NOTE : While this is generally a non-credit-bearing course, you may able to use this class with proper completion for 3 credits (1 course) toward a bachelor's degree at Southern New Hampshire University.
Coaching
If you are enrolled in the verified track (paid track) in any course that is a part of a MicroBachelors program, including this course, you are eligible for coaching at no additional cost. Please note that coaching is only available via SMS to U.S. phone lines.
Our coaches (real humans) are ready to help you with career exploration, navigating resources, staying motivated, and solving problems along the way to your goals.
Learn more about the value of coaching directly from one of our coaches, Erin.
Knowledge
- Collect and classify data
- Summarize data using visual and numeric techniques
- Quantify answers to questions about estimating parameters using hypothesis test and confidence interval techniques
- Quantify answers to questions about correlation between variables using linear regression techniques
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