GIS and RS:

The GIS component has been designed to introduce students to the fundamentals of GIS. It is a lecture/lab based course with an emphasis on applied learning. The lecture portion of the class focuses on the basic functions and applications of GIS, data sources and management techniques, vector and raster models, database development, spatial analysis, and visualisation. The sub-module of Remote Sensing focuses on various spatial data sources and their specifications, their modes of acquisition and processing. In addition, it allows the students to acquire the basic knowledge about the principles of Electromagnetic Radiation, the propagation of EM radiation through space, the atmosphere and the interaction with matter (Earth matter obviously is our concern).

1. Brief description of aims and content

This course will cover topics related to Descriptive (measure of central tendency and measure of dispersion) and inferential (confidence interval and Hypothesis Testing) statistical analysis methods with commonly used type of probability distribution (such as Binomial, Poisson, Gaussian (Normal) and chi-square). The main aim of the course is to introduce and able students to apply different methods of statistical analysis and probability theory according to the type of data available or collected.

2. Learning Outcomes

2. 1 Knowledge and Understanding

Upon Completion of this Module students,

1. should have a reasonable understanding of the definitions and terms related to the Module aims as well as the Course Contents.
2. Should have a reasonable understanding of the type of statistical methods of data Analysis according to the data type.
3. Should be able to present and summarize statistical data using appropriate Graphs and Tables.
4. Should be able to interpret the result obtained by different statistical analysis and application of probability

2.2        Cognitive/Intellectual skills/Application of Knowledge

Having successfully completed the module, students should be able to:

1. Develop their Problem solving Skills related to the application of Probability theory and Statistical method of data analysis.
2. Have a reasonable knowledge about type of statistical data with corresponding type of statistical analysis

2.3        Communication/ICT/Numeracy/Analytic Techniques/Practical Skills

Having successfully completed the module, students should be able to:

1. Analyze the statistical data by applying appropriate method of data analysis and Probability theory.
2. Present and interpret the output of different statistical analysis method and probability theory.

2.4        General transferable   skills

Having successfully completed the module, students should be able to:

1. Able to analyse, present and make interpretation related to a given statistical data.
2. Have a general insight as descriptive and inferential analysis can be done using SPSS.

    Indicative Content

Descriptive and Inferential statistical Analysis methods (Mean, Median, Mode, Range, Interquartile Range, Variance, Standard Deviation, Confidence Interval, Hypothesis Testing), Data presentation using appropriate graphs (Bar, Histogram, Frequency polygon, Pie etc) and Tables (Frequency distribution, 2X2 Table), Introduction to probability theory and spaces, Application of different probability distribution (Binomial, Poisson, Chi-square, Normal)according to type of variable/data, Sample size determination and sampling techniques; inference using confidence interval and hypothesis testing, tests of significance, simple regression and correlation, application of different statistical control charts.

 Learning and Teaching Strategy

The course is delivered mainly through lectures backed up by tutorial sessions.

The lecture includes interactive elements whereby students in groups apply principles to simple problems to ensure their involvement and so gain understanding.  Handouts are used so that students can concentrate on the material of the lecture. Problem sheets are given out to students and after time, the problems are discussed in class.  Some of the problems will be handed in and then marked by peers to give formative feedback to fellow students.

The assignment will require the students to undertake some investigation on their own and to develop ideas and apply them. 

  ASSESSMENT STRATEGY

The assessment strategy is:

• to assess knowledge and application skills through written examination. As a process of Continuous assessment, students are also given Assignment, Quiz, Mini Project. The students therefore will not just rely on memory but also show understandings of the principles in application to exam problems.
• to assess self learning, understanding and application through the assignment which will be ‘open ended’ so that the student has to some extent formulate the problem and  its solution.

Assessment Criteria:

• For the examination setting and marking the UR-CST generic marking criteria will be used.
• For the assignment, criteria will be drawn up appropriate to the topic, based on the UR-CST generic marking criteria. 

• Assisgnments: 10
• Quizzes: 10
• CATs: 30
• Final Exam: 50
• Passmark: 50

  Strategy for feedback and student support during module 

• Interactive lecturing style, with opportunities for questions, and requirement to work on simple problems.
• Tutorial classes where students can ask questions and be lead through solutions as required.

• Opportunities to consult lecturer and/or tutorial assistant in office hours.

     Indicative Resources

Core Text

1.Introduction to probability theory: Ito, Kiyosi – New York: Cambridge University Press, 1978

ISBN : 3540606297, 9783540606291, 978-3540606291

2. J.N. Kapoor and H.C. Saxena, Mathematical Statistics ISBN : 8121912466, 9788121912464,

Journals

1. 1.       Journal of Applied probability and Statistics SJR - Sankhya: The Indian Journal of Statistics www.scimagojr.com/journalsearch.php

Key websites and on-line resources

Applied probability

(http://unjobs.org/tags/applied-probability)

Teaching/Technical Assistance

                1 Lecturer,

                1 Tutorial assistant

Laboratory space and equipment

None

Computer requirements

Introduction to SPSS

Others

 PLEASE ADD ANYTHING ELSE YOU THINK IS IMPORTANT        

  TEACHING TEAM

Mr. Jean de Dieu NIYIGENA

Email: jniyigena@aims.ac.tz

Phone: +250786687217

Office: P004 Muhabura Block

The course of Research Methodology aims:
• To facilitate a basic understanding of main principles, structure and methods of research to prepare research projects for B.Sc. Degree.
•It covers Principles and Concepts of Research, Research Tools and Methods, Structure and planning research, Literature review, Role of Data in Research, Statistical Techniques for Data Analysis, Research Budget and Resources. Proposal writing.

This course of Analytical Chemistry aims to give to the students the essential of theoretical
and practical foundations for quantitative analysis of chemical reactions in solution.