Overview
Fundamentals of Statistics at Massachusetts Institute of Technology - MITx is part of the MITx MicroMasters program in Statistics and Data Science. It is the science of turning data into insights and ultimately decisions. Behind recent advances in machine learning, data science and artificial intelligence are fundamental statistical principles.
Key facts
The purpose of this class is to develop and understand these core ideas on firm mathematical grounds starting from the construction of estimators and tests, as well as an analysis of their asymptotic performance.
After developing basic tools to handle parametric models, we will explore how to answer more advanced questions, such as the following:
- How suitable is a given model for a particular dataset?
- How to select variables in linear regression?
- How to model nonlinear phenomena?
- How to visualize high-dimensional data?
Taking this Fundamentals of Statistics certificate at Massachusetts Institute of Technology - MITx will allow you to expand your statistical knowledge to not only include a list of methods, but also the mathematical principles that link them together, equipping you with the tools you need to develop new ones.
This course is part of theMITx MicroMasters Program in Statistics and Data Science. Master the skills needed to be an informed and effective practitioner of data science. You will complete this course and three others from MITx, at a similar pace and level of rigor as an on-campus course at MIT, and then take a virtually-proctored exam to earn your MicroMasters, an academic credential that will demonstrate your proficiency in data science or accelerate your path towards an MIT PhD or a Master's at other universities.
Programme Structure
What you'll learn
Construct estimators using method of moments and maximum likelihood, and decide how to choose between them
Quantify uncertainty using confidence intervals and hypothesis testing
Choose between different models using goodness of fit test
Make prediction using linear, nonlinear and generalized linear models
Perform dimension reduction using principal component analysis (PCA)
Key information
Duration
- Part-time
- 4 months
- 10 hrs/week
Start dates & application deadlines
Language
Delivered
Campus Location
- Portland, United States
Disciplines
Statistics View 110 other Short Courses in Statistics in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
To obtain additional information about the program, we kindly suggest that you visit the programme website, where you can find further details and relevant resources.
Tuition Fees
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International Applies to you
Applies to youNon-residents300 USD / full≈ 300 USD / full - Out-of-State300 USD / full≈ 300 USD / full
Additional Details
- Add a Verified Certificate for $300 USD
- Limited access: free