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أ.1 |
Understand the covariate concepts and distinguish it from a moderator . |
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أ.2 |
Recognize the case where ANCOVA is a defensible statistical approach for analyzing the data . |
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أ.3 |
Understand the basic concepts of GLM , logistic and Poisson regression . |
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أ.4 |
Understand bootstrap and resampling applications .. |
ب. (Mental skills)
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ب.1 |
Student should be able to analyze , interpret , and write up results for ANCOVA . |
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ب.2 |
Student should be able to conduct generalized linear model . |
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ب.3 |
Student should be able to conduct and interpret logistic and Poisson regression . |
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ب.4 |
Student should be able to apply bootstrap and resampling applications in regression . |
جـ - (Practical & professional skills)
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ج.1 |
The ability to find the suitable ANCOVA models. |
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ج.2 |
The ability to apply GLM . |
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ج.3 |
The ability to select the best fitted logistic regression model for a given set of data . |
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ج.4 |
The ability to select the best order polynomial regression model for a given set of data . |
د - (Generic and transferable skills)
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د.1 |
Student will be able to apply different ANCOVA models. |
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د.2 |
Student will be to find the confidence intervals-bootstrapping in regression . |
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د.3 |
Student will be able to communicate the methods used and results in form understandable to the non-statistician . |
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د.4 |
Establish a competitive environment between students. |
Teaching and learning methods
Exercises
· Lectures
· To use statistical programs
· Discussion of Field Training
· Research
Methods of assessments
(Assessment table)
Rating No. | Evaluation methods | Evaluation Duration | Evaluation weight | Percentage | Rating Date (Week) | Reviews |
First Assessment | First Exam | 2 | 20 | 20% | Fifth week |
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Second Assessment | Second exam | 2 | 20 | 20% | Week Eleven |
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Third Assessment | Practical exam | 2 | 10 | 10% | Week Thirteen |
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Final Evaluation | Final Exam | 2 | 50 | 50% | Commitment to the final schedule |
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Total | 100 degree | 100% |
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Course (contents)
Scientific topic | Number of Hours | Lecture | laboratory | Exercises | Number of weeks |
Covariance with one concomitant variable | 12 | 6 | 4 | 2 | 3 |
Heterogeneity by analyzing the single and binary variance of a single associated variable. | 12 | 6 | 4 | 2 | 3 |
The basic concept of generalized linear models. | 8 | 4 | 3 | 1 | 2 |
Logistic regression, Poisson regression, nonlinear models and polynomial regression. | 12 | 6 | 4 | 2 | 3 |
Boot and remodel, bias, standard error, confidence intervals and regression. | 12 | 6 | 4 | 2 | 3 |
(References )
Bibliography | Publisher | Version | Author | Where it is located |
Rapporteur notes | Notes prepared by the course instructor |
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Textbooks | Wiley 8th edition | Design and Analysis of Experiments | Montgomery. D. C |
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Help Books | Chapman & Hall/CRC | Statistical Computing with R | Rizzo, M.L |
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Scientific Journals | ||||
Internet Sites | ||||
Other | Springer | An Introduction to Statistical learning with Applications in R | James, G., Witten, D., Hastie, T., and Tibshirani |
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