You must be logged in to take this course → LOGIN | REGISTER NOW
This course is a self-contained introduction to statistics with economic applications. Topics such as elements of probability theory, sampling theory, statistical estimation, regression analysis, and hypothesis testing will be discussed in this course. It uses elementary econometrics and other applications of statistical tools to economic data. It also provides a solid foundation in probability and statistics for economists and other social scientists.
Assessment
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
Certification
Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.
Having an Official Edukite Certification is a great way to celebrate and share your success. You can:
- Add the certificate to your CV or resume and brighten up your career
- Show it to prove your success
Course Credit: MIT
Course Curriculum
| Set and Probability Theory | 00:10:00 | ||
| Random Variables, Probability Mass Density Function, and Cumulative Distribution Function (Univariate Model) | 00:10:00 | ||
| Multiple Random Variables, Bivariate Distribution, Marginal Distribution, Conditional Distribution, Independence, Multivariate Distribution (Multivariate Model) | 00:15:00 | ||
| Expectation (Moments) | 00:15:00 | ||
| Random Variable and Random Vector Transformations (Univariate and Multivariate Models) | 00:10:00 | ||
| Special Distributions (Discrete and Continuous) | 00:10:00 | ||
| Graph Representation Special Distributions | 00:10:00 | ||
| Random Sample, Law of Large Numbers, Central Limit Theorem | 00:10:00 | ||
| Simulations Magnifying Glass | 00:05:00 | ||
| Point Estimators and Point Estimation Methods | 00:15:00 | ||
| An Overview | 00:02:00 | ||
| Interval Estimation and Confidence Intervals | 00:10:00 | ||
| t-Student versus Standard Normal A Graphical View | 00:02:00 | ||
| Hypothesis Testing | 00:20:00 | ||
| An Applied Review | 00:10:00 | ||
| Assessment | |||
| Submit Your Assignment | 00:00:00 | ||
| Certification | 00:00:00 | ||
Course Reviews
No Reviews found for this course.
