MASENO UNIVERSITYF O U N T A I N O F E X C E L L E N C E

Master of Science in Research Methods (eRM)eLearning ProgrammeSCHOOL OF MATHEMATICS, STATISTICS AND ACTUARIAL SCIENCE, DEPARTMENT OF STATISTICS AND ACTUARIAL SCIENCE

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IntroductionThis programme leads to the degree of Master of Science in Research Methods with specialisation in either Biological or Social Research Methods. The program is designed with students in full-time employment in mind. It is a practical course in which the involvement of the employer is desirable in as far as they could permit the use of their data and problems in content delivery. Towards this end, the programme shall, where possible, be tailored to suit the needs of such employers. On the overall, this innovative approach hopes to further the relevance of this programme to industry.

Background

The taught part of this course consists of a series of modules. Each module is the equivalent of 2 weeks full-time teaching or 48 contact hours, as are other MSc courses offered at Maseno University. A module can be taken either as part of a planned MSc course, or as a stand-alone module.

The modules are delivered in various ways that are deemed appropriate for the program and which accords flexibility to the leaner. These are: fully online, blended, face-to-face evening and weekend; and specially scheduled intensive learning sessions. It is important to note that the use of Maseno University’s Learning Management System shall form a significant part of content delivery in all these modes of learning.

Objectives

The objectives of the programme are:a. To train professionals in research methods which are immediately applicable in their work place.b. To expose students to various branches of statistics and research methods. c. To prepare students for professional doctorate or PhD in Applied Statistics or Research Methods.

Admission requirements for the student

To be eligible for registration for the Master of Science (M.Sc.) programme, a candidate shall: a. Provide evidence of an academic qualification of at least or equivalent to either:i. An upper second class honours degree of Maseno University ii. Lower second class honours degree of Maseno University with statistics as a major subject.b. Poses basic computer skills since all modules will make

use of the University internet-based Learning Management System.c. Poses basic statistical skills consistent with the topics taught in undergraduate courses.

Duration and structure of the Programme

Students will choose to register for the MSc program on completion of some or all of the modules in the course of their study. The duration of the program, therefore, shall depend on a student’s preference. In order to qualify for the award of the degree, a student shall: i. Take all prescribed Core modules in the respective specialisationii. Take at least 12 modules including Core modulesiii. Produce either an academic Project Report equivalent to 4 modules or a Thesis equivalent to 8 modules

Examinations

The examinations for an individual module shall be conducted as per the Maseno University examination policy, which includes the following: i. The university examination rules and regulations for Postgraduate Studies shall applyii. Sit-in examinations shall normally be held at the end of the semester in which the modules are offered.iii. Modules will normally be assessed by one three-hour written examination constituting 60% and continuous assessment tests constituting 40%. iv. The written report for the project shall constitute 60% and oral examination shall constitute 40%.v. The examination pass mark for each module shall be 50%.

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Course Outine

The taught part of the programme consists of a minimal set of core modules together with optional modules.

Assumptions:1. There are 2 distinct areas of specialization, namely Biological (B) and Social Science (S) – related area.2. The core (C) and Elective (E) modules shall depend on the chosen area of specialization such as CB (Core Biological) and EB (Elective Biological). Where there is a common module, the module shall be a (CB, CS)-type or (EB, ES)-type etc.3. Modules are offered at two levels, namely level 8 and level 9.4. The level 9 modules are elective (E type) modules. Thus C-type modules are only with respect to level 8 modules, except for the project.

A. Biological area

Core ModulesCode Title Type Units*MRM 805: Computational matrix Analysis (CB, CS) 1MRM 807: Linear Statistical Models I (CB, CS) 1MRM 831: Statistical Theory (CB, CS) 1MRM 833: Interactive Data Analysis (CB, CS) 1MRM 834: Multivariate Statistics (CB, CS) 1MRM 890: Project (CB,CS) 4

Elective Modules Code Title Type UnitsMRM 804: Non parametric Statistical Analysis (EB) 1MRM 808: Design and Analysis of Experiments (EB) 1MRM 811: Bayesian Statistics (EB) 1MRM 812: Applied Time Series Analysis (ES, EB) 1MRM 813: Analysis of Categorical Data (ES, EB) 1MRM 814: Analysis of Longitudinal Data (ES, EB) 1MRM 815: Epidemiological Methods (EB) 1MRM 816: Design of Clinical Experiments (EB) 1MRM 817: Linear Statistical Models II (EB) 1MRM 819: Model Selection and Inference (EB) 1MRM 820: Statistical Demography (EB) 1MRM 821: Statistical Ecology (EB) 1MRM 822: Statistics for Psychosocial Research (ES, EB) 1MRM 823: Statistics in Industrial Biotechnology (EB) 1MRM 824: Topics in Biometry (EB) 1

Code Title Type Units MRM 825: Exploring, describing and presenting data (EB, ES) 1MRM 826 Communicating research (EB, ES) 1MRM 832: Survey Sampling (EB) 1MRM 835: Survival Data Analysis (EB, ES) 1MRM 836: Applied Stochastic Processes (EB) 1MRM 846: Climatic Variability and Climate Change (EB, ES) 1MRM 847: Statistical Computing (EB, ES) 1

B. Social area

Core ModulesCode Title Type UnitsMRM 802: Stochastic Processes I (ES) 1MRM 805: Computational matrix Analysis (CB, CS) 1MRM 807: Linear Statistical Models I (CB, CS) 1MRM 831: Statistical Theory (CB, CS) 1MRM 833: Interactive Data Analysis (CB, CS) 1MRM 834: Multivariate Statistics (CB, CS) 1MRM 837: Design and Analysis of Surveys I (CS) 1MRM 890: Project (CB,CS) 4

Elective ModulesCode Title Type UnitsMRM 804: Non parametric Statistical Analysis (EB,ES) 1MRM 812: Applied Time Series Analysis (EB, ES) 1MRM 813: Analysis of Categorical Data (EB, ES) 1MRM 814: Analysis of Longitudinal Data (EB, ES) 1MRM 822: Statistics for Psychosocial Research (EB, ES) 1MRM 825: Exploring, describing and presenting data (EB, ES) 1MRM 826: Communicating research (EB, ES) 1MRM 827: Design and Analysis of Surveys II (ES) 1MRM 828: Advanced Quantitative Economics (ES) 1MRM 829: Applied Demography (ES) 1MRM 830: Survey Research Methods and Observation Studies (ES) 1MRM 835: Survival Data Analysis (EB, ES) 1MRM 838: Modelling and Analysis of Social Data (ES) 1MRM 839: Advanced Econometrics (ES) 1MRM 840: Analytic Demography (ES) 1MRM 845: Topics in Social Statistics (ES) 1MRM 846: Climatic Variability and Climate Change (EB, ES) 1MRM 847: Statistical Computing (EB, ES) 1