A.1 | The student is introduced to new methods and solutions to some statistical problems when studying the course |
A.2 | The student learns how to estimate regression model parameters and their hypothesis tests |
A.3 | The student learns how to deduce some statistical indicators using regression analysis |
In. Mental (skills)
B.1 | Ability to construct and characterize a regression model. |
B.2 | Ability to evaluate regression models and determine the appropriate choice from different regression models. |
B.3 | The student becomes able to use regression to analyze the data and adopt its results remotely to extract scientific indicators that determine the dimensions of the phenomenon under study |
c. Practical & Professional (Skills)
C.1 | Ability to analyze regression models and interpret results. |
C.2 | The student diagnoses the question in terms of available data |
C.3 | The student deduces indicators that describe the extent to which the theoretical model is associated with experimental reality |
W. Generic (and transferable skills)
D.1 | The ability to use ready-made statistical programs in regression analysis. |
D.2 | The ability to analyze the data under study using regression analysis. |
D.3 | The ability to choose the appropriate regression model for the data under study from among several available models. |
Teaching and learning methods
Lectures
· Exercises
· Practical applications using ready-made statistical programs
Methods of assessments
(Assessment table)
Rating No. | Evaluation methods | Evaluation Duration | Evaluation weight | Percentage | Rating Date (Week) | Reviews |
First Assessment | Midterm exam |
| 20 | 20% | 7 |
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Second Assessment | Half Exercises |
| 10 | 10% |
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Third Assessment | Second midterm exam |
| 20 | 20% | 14 |
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Fourth Assessment | Final Exam |
| 50 | 50% | 16 |
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Total | 100 degree | 100% | ||||
Course (contents)
Scientific topic | Number of Hours | Lecture | laboratory | Exercises | Number of weeks |
The concept of regression: | 4 | 2 | 2 |
| 1 |
Simple linear regression: - If there is no repetition of the values of the independent variable : : If there is a repetition of the values of the independent variable.
| 12 | 8 | 2 | 2 | 3 |
Irregularities or defects in the hypotheses of the analysis of the simple regression model detected and corrected:
| 10 | 4 | 4 | 2 | 2.5 |
MultipleRegression:
| 12 | 8 | 2 | 2 | 3 |
Simple nonlinear regression:
| 10 | 6 | 2 | 2 | 2.5 |
Functionvariables:
| 8 | 4 | 2 | 2 | 2 |
(References)
Bibliography | Publisher | Version | Author | Where it is located |
Rapporteur notes | Course Professor's Memoirs |
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Textbooks | John wiley and Sons |
| Draper , N and Smith | Library |
Help Books | Richard D. Irwin, INC. | Applied Linear Statistical Models | J. Neter& W. Wasserman | Library |
Scientific Journals | ||||
Internet Sites | ||||
Other |
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