The course introduces a standardized approach for parameter estimation, using a functional model (relating the observations to the unknown parameters) and a stochastic model (describing the quality of the observations). Using the concepts of least squares and best linear unbiased estimation (BLUE), parameters are estimated and analyzed in terms of precision and significance. This course teaches how to translate real-life estimation problems to easy mathematical models.
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:
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- Show it to prove your success
Course Credit: TU Delft
Course Curriculum
| Module: 01 | |||
| Introduction video: measuring the canal width | 00:05:00 | ||
| Course video | 00:02:00 | ||
| Course team | 00:02:00 | ||
| Module: 02 | |||
| What is an “estimation problem”? | 00:08:00 | ||
| Deterministic and stochastic variables | 00:04:00 | ||
| Quality of measurements | 00:05:00 | ||
| Random errors | 00:04:00 | ||
| Precision and covariance matrix | 00:04:00 | ||
| Precision and covariance matrix (cont’d) | 00:05:00 | ||
| Elements of the estimation problem | 00:04:00 | ||
| 1. Feedback video | 00:03:00 | ||
| Module: 03 | |||
| Introduction video: sea level rise | 00:04:00 | ||
| Model formulation | 00:05:00 | ||
| The functional model: connecting the elements | 00:05:00 | ||
| Sea level example | 00:05:00 | ||
| Solvability of a system of equations | 00:05:00 | ||
| Uniqueness of solutions | 00:02:00 | ||
| Overdetermined systems | 00:04:00 | ||
| Stochastic model | 00:04:00 | ||
| Stochastic model (cont’d) | 00:05:00 | ||
| 2. Feedback video | 00:02:00 | ||
| Module: 04 | |||
| Concept of Least Squares | 00:05:00 | ||
| Least Squares: Analytical solution | 00:05:00 | ||
| Weighted Least Squares Estimation | 00:08:00 | ||
| Deriving the equations | 00:07:00 | ||
| Geometry of least squares | 00:06:00 | ||
| Geometry of least squares – example | 00:04:00 | ||
| 3. Feedback video | 00:04:00 | ||
| Module: 05 | |||
| Estimate vs Estimator | 00:04:00 | ||
| Estimator Properties | 00:05:00 | ||
| An introduction to BLUE | 00:07:00 | ||
| Elaboration on BLUE | 00:09:00 | ||
| Non-linear Least Squares: Introduction | 00:06:00 | ||
| Non-linear Least Squares: Principle | 00:07:00 | ||
| Non-linear Least Squares: Solution and Properties | 00:08:00 | ||
| 4. Feedback video | 00:05:00 | ||
| Module: 06 | |||
| Precision | 00:03:00 | ||
| Error Propagation (1) | 00:05:00 | ||
| Error Propagation (2) | 00:06:00 | ||
| Estimator Precision and Confidence Interval (1) | 00:04:00 | ||
| Estimator Precision and Confidence Interval (2) | 00:05:00 | ||
| Module: 07 | |||
| 5. Feedback video | 00:02:00 | ||
| Error Detection: Introduction | 00:05:00 | ||
| Error Detection: Overall Model Test | 00:07:00 | ||
| Overal Model Test: Interpretation | 00:03:00 | ||
| Overal Model Test: Interpretation (cont.) | 00:07:00 | ||
| Module: 08 | |||
| 6. Feedback video | 00:04:00 | ||
| Closing video | 00:07:00 | ||
| Module: 09 | |||
| Mat 1.1 What is MATLAB? | 00:02:00 | ||
| Mat 1.2 MATLAB Online | 00:02:00 | ||
| Mat 1.3 MATLAB Variables | 00:03:00 | ||
| Mat 1.4 MATLAB Functions | 00:03:00 | ||
| Mat 1.5 MATLAB as a Calculator | 00:02:00 | ||
| Module: 10 | |||
| Mat 2.1 Creating Vectors | 00:01:00 | ||
| Mat 2.3 Matrix Creation Functions | 00:02:00 | ||
| Mat 2.4 Combining Matrices | 00:02:00 | ||
| Module: 11 | |||
| Mat 3.1 Accessing Elements of a Matrix | 00:02:00 | ||
| Mat 3.2 Logical Variables | 00:03:00 | ||
| Mat 3.3 Accessing Elements of a Vector Using Conditions | 00:02:00 | ||
| Mat 3.4 Determining Array Size and Length | 00:02:00 | ||
| Mat 3.5 Statistical Functions on Matrices | 00:02:00 | ||
| Mat 3.6 Calculations with Matrices | 00:02:00 | ||
| Module: 12 | |||
| Mat 4.1 Making Histograms | 00:03:00 | ||
| Module: 13 | |||
| Mat 5.1 If-Else Statements | 00:03:00 | ||
| Mat 5.2 Writing a FOR Loop | 00:02:00 | ||
| Mat 5.3 Writing a WHILE Loop | 00:03:00 | ||
| Assessment | |||
| Submit Your Assignment | 00:00:00 | ||
| Certification | 00:00:00 | ||
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