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Computer systems in a network environment require significant expertise to administer, troubleshoot, and tune. This course presents the advanced tools and techniques needed to configure and to control (UNIX, Linux, Windows) machines and their peripherals. It then expands upon this information in a network environment. Finally, performance problems are discussed and a general methodology is defined for isolating/resolving performance problems.

 This course unit aims at equipping students with in-depth regression analysis and related Techniques.  The course will involve simple and multiple linear regressions (OLS); matrix representation of the regression model; statistical inferences (correlation analysis, T-test, F-test CHi2 test, ANOVA) for regression model; properties of OLS; diagnostics and remedies for multicollinearity and heteroskedasticity; diagnostics for model selection, variable selection, transformations (such as log, Box-Cox, etc.); appropriate Statistical packages (e.g. STATA) will be used in the course unit to demonstrate how to apply the Techniques on real data.

Model specification and data: developing a conceptual framework; types and sources of data, data mining, model specification and data generation; the mathematical Programming approach to policy analysis: the classical MP models, limitations of of MP models and extension to positive mathematical Programming, classification of mathematical Programming models commonly used in policy analysis, application in hypothesis testing, application in analyzing policy instruments and commodity policy, application in forecasting; econometric approach to policy analysis.

Classification of econometrics models, linear and none linear models, limited and censor-dependent variable approaches (logit, probit, tobit, and their extensions such as multinomial logit and probit etc.), system of equations or simultaneous equations, application in hypothesis testing, application in analyzing policy instruments and commodity policy, application in forecasting, the problem of causality in policy analysis, limitation of econometric models; impact assessment: propensity score matching, regression discontinuity designs, panel data to analyze with staggered entry.

·         Introduction to Econometrics Preview

·         Simple Linear Regression: Basic Concepts

·         Simple Linear Regression: Estimation of Parameters

·         Simple Linear Regression: Outliers

·         Multiple Linear Regression: Basic Concepts

·         Multiple Linear Regression: Estimation of Parameters

·         Autocorrelation: Durbin-Watson Test Statistic

·         Multivariate Regression

·         Logistic Regression

·         Polynomial Regression

·         Autoregressive Model

·         Vector Autoregressive Model

.         Limited and censor-dependent variable approaches (logit, probit, tobit, and                their extensions such as multinomial logit and probit etc.),

Detailed Course Content

Referencences:

Econometrics (2022) by Bruce Hansen, recommended but not required.

https://www.ssc.wisc.edu/~bhansen/econometrics/

Other complementary Texts include:

Angrist, J.D. and J. Pischke (2009): Mostly Harmless Econometrics - An Empiricists Companion, Princeton University Press

Amemyia, T. (1985): Advanced Econometrics, Blackwell

Berndt, E.R., The Practice of Econometrics: Classic and Contemporary. Addison-Wesley, 1991.

Chow, G. C. Econometrics. McGraw Hill, 1983.

Cameron, A. C. and Travedi, P.K. (2005): Microeconometrics – Methods and Applications, Cambridge University Press

Davidson, R. and McKinnon, J.G. (1993): Estimation and Inference in Econometrics, Oxford University Press

Drhymes, P. (1994) Topics in Advanced Econometrics, Vol 2: Linear and Nonlinear Simultaneous Equations, Springer Verlag

Green, W.A., Econometric Analysis, 8th edition, Prentice Hall.

Goldberger, A. S., A Course in Econometrics. Harvard University Press, 1991.

Hayashi, F. (2000). Econometrics. Princeton: Princeton University Press

Malinvaud, E. Statistical Methods of Econometrics, 3rd Edition. North-Holland, 1980.

Ramanathan, R. Statistical Methods in Econometrics, Academic Press, 1993.

Ruud, P.A. (2002): An Introduction to Classical Econometric Theory, Oxford University Press.

Sargan, J. D. Lectures on Advanced Econometric Theory. Basil Blackwell, 1988

Wooldridge, J.M . (2002): Econometric Analysis of Cross-Section and Panel Data, MIT Press.

Schervish, M.J. (1995): Theory of Statistics, Springer Verlag

Spanos, A. Statistical Foundation of Econometric Modeling. Cambridge University Press, 1986.

Theil, H. (1971): Principles of Econometrics, Wiley

White, H. (2000): Asymptotic Theory for Econometricians (Revised Edition), Academic Press

Zellner, A. An Introduction to Bayesian Inference in Econometrics. Wiley-Interscience, 1996.

 Gurmu, Shiferaw, and Pravin K. Trivedi, (1996)"Excess Zeroes in Count Models for Recreational Trips." Journal of Business and Economics Statistics 14: 469-477.
  

 Blundell, Richard, Rachel Griffith, and Frank Windmeijer, (1984)"Individual Effects and Dynamics in Count Data Models," London: Institute for Fiscal Studies Working Paper No. W99/3 (1999).

Hausman, Jerry A., Zvi GriliLHes, and Bronwyn H. Hall, "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica 52: 909-938.

Hall, Bronwyn H., Zvi GriliLHes, and Jerry A. Hausman, (1986)"Patents and R&D: Is There a Lag?" International Economic Review 27: 265-283.

Montalvo, Jose Garcia, (1993) "GMM Estimation of Count Panel Data Models with Fixed Effects and Predetermined Instruments," Journal of Business and Economic Statistics 15: 82-89.

LHamberlain, Gary, "Multivariate Regression Models for Panel Data, (1982)" Journal of Econometrics 18:5-46.

Exercise Collections:

P. C. B. Phillips and M. R. Wickens, Exercises in Econometrics, Vol. I & II. Allen/Ballinger, 1978.

K. Abadir and J. Magnus, Econometric Exercises Vol 1: Matrix Algebra. Cambridge University Press, 2005.

Hello and welcome to the Audio production class. We look forward to getting to know each of you and learning together.  During the course of the study semester we will together cover these key broad areas:

●      Nature of sound and how it is transmitted.

●      Audio facilities/equipment-both analog and digital

●      Radio production tools.

●      The process of producing good quality audios

In order to ensure we progress in an orderly way, everyone will be expected to read, listen to assigned audio materials and write about them, and present audio projects. I encourage you to go beyond assigned materials as the more broadly you read, the more sense this course will make. The end will be a submission of an audio project.

Teaching and learning methods will be varied and will include face to face and online lectures, small group discussion, independent study and presentation.

This course is designed by the Faculty of Science and Technology to equip all university students with the basic knowledge and skills in computing. It seeks to demystify computers and their use through lectures and practical lab sessions.

It introduces students to the basic concepts of Information Technology, the use of the Internet and office applications like a word processor and spreadsheets.

The course is spread over a period of 14 weeks which is the order this Student Workbook follows. You are required to follow through each week and attempt exercises at the end of each week.

This course is designed by the Faculty of Science and Technology to equip all university students with the basic knowledge and skills in computing. It seeks to demystify computers and their use through lectures and practical lab sessions.

It introduces students to the basic concepts of Information Technology, the use of the Internet and office applications like a word processor and spreadsheets.

The course is spread over a period of 14 weeks which is the order this Student Workbook follows. You are required to follow through each week and attempt exercises at the end of each week.

Question one:

a. Select a real-world business or industry (e.g., agriculture, manufacturing, or technology). Describe a scenario where the business has to make a decision between two types of products or services. Draw a PPF for this scenario and discuss the potential opportunity costs and trade-offs involved.

b. Discuss how factors such as technological advancement or an increase in resources can shift the PPF. Use a graph to show the effect of such changes on the PPF for the chosen industry. How do these shift’s impact business decisions and economic growth?

Commercial graphic design is about and takes part in packaging and marketing by providing designs for labels, trademarks, colophons, and advertising materials (such as posters, catalogs, booklets, banners, prospectuses etc). Commercial graphic designers also provide such materials vital to industry as business forms and envelopes.

This is a research methodology course that focuses on developing researching and writing skills in Computer Science & Engineering Domain. As the Computer Scientist, software developer, software engineer, research requires multidisciplinary approach. Many of the concepts are borrowed from social science, Psychology, Statistics, and other domains. Here we investigate the empirical research methods for their applicability and suitability to a research problem. As each of them comes with their strengths and weakness, perhaps a feasible, mix of such methods should provide greater insight and understanding in order to derive useful contributions.