Most sectors of human endeavor raw data. Thus there is a lot of raw data that is usually stored in computer discs. Such undigested data is of no use until we can start to make sense of it. Statistics is an informative science in fact the science and art of extracting meaning from seemingly incomprehensible data. This enables one to make sound decisions.
Statistics is a practical discipline which helps us to solve real problems in the real world. The field of statistics provides the scientist with some of the most useful techniques for evaluating ideas, testing theory and discovering the truth. The scientist thus can make informed decisions by using statistical methods. Statistics has applications in Bioinformatics, Biostatistics, Computing (Statistical computing is a highly sought skill), and Economics, Finance, Psychology, Physics and Health industry. In all these fields evidence based decision making impacts positively in proper utilization of available resources and spur Economic growth. Proper utilization of available resources in all sectors of an economy can accelerate the attainment of the aspirations of Vision 2030. The delivery of the programme is based on inter-faculty collaboration and use of Information Technology (IT).
The aim of this programme is to provide students with the opportunity to develop confidence and skills to apply statistical principles to solve practical problems in industry and public service.

OBJECTIVES
At the end of this programme, the student will be able to:-
a)    Explain fundamental principles of the Theory and Methods of Statistics.
b)    Apply Statistical Methods and Survey Techniques to a wide range of practical problems.
c)    Analyse large data sets using Statistical Computing Techniques.
d)    Employ Statistical Methods necessary in making evidence based decisions.

1.    Admission Requirements
1.1.    Candidates must satisfy the University’s general admission criteria for undergraduate programmes.
1.2.    Eligibility for consideration for admission into the Degree of Bachelor of Science in Statistics at the School of Mathematics shall be governed by the following minimum admission requirements or an equivalent qualification recognized by Senate:
1.2.1.    KCSE: A holder of Kenya Certificate of Secondary Education (KCSE) with minimum mean aggregate of C+. In addition candidates must have obtained a minimum grade of B in mathematics
1.2.2.    A-level: A holder of Kenya Advanced Certificate of Education (KACE) with two Principal passes in Mathematics/Physics, Mathematics/Chemistry, Mathematics/Geography or Mathematics/Economics.
1.2.3.    Diploma in Computer Studies/Statistics: A holder of ordinary diploma in Computer Studies or Statistics with a minimum pass at credit level from an institution recognized by Senate.
1.2.4.    Diploma in Education: A holder of ordinary diploma in Education with Mathematics as a major subject from an institution recognized by Senate.

2.    CREDIT TRANSFER AND EXEMPTIONS
The point of entry into the programme for candidates other than direct KCSE shall be approved by Senate or recommendation of Board of the School of Mathematics and shall be based on the qualification of the candidate.

2.1.    Credit Transfer
2.1.1.    A candidate who has been admitted into this programme and has taken and passed a course unit offered within another degree programme, may apply for transfer of credit earned in the former programme to this programme.
2.1.2.    Transfer will only be approved from institutions and degree programmes recognized by Senate.
2.1.3.    Where a candidate wishes to transfer credit from a degree programme of another institution to this programme, the candidate shall send an application to the Academic Registrar justifying the request and provide evidence of the credentials which support such a request.
2.1.4.    Credit may not be transferred for course units in the third and fourth year of study.
2.1.5.    Application for exemption shall be considered only after the applicant has paid an exemption fee.

3.  COURSE STRUCTURE AND DURATION
3.1.    The course shall extend over a minimum of 8 semesters and a maximum period of 16 semesters.
3.2.    Each academic year shall have two semesters of 15 weeks.
3.3.    A course unit shall be defined as 45 contact hours of lectures, tutorials and computer practicals; including common undergraduate courses.
3.4.    The mode of delivery is organized via a combination of lectures, compulsory reading, laboratories and homework. Teaching will be done face to face lectures and open, distance and e-learning (ODeL).
3.5.    In the first year of study, a candidate is required to take all the four core course units. STA101, STA 103, STA121 and STA 122, plus the following Mathematics course units SMA101, SMA103,SMA104,SMA105 and SMA 108. There are also three common undergraduate courses: CCS001, CCS008 and CCS010.
3.6.    In the second year of study, a candidate is required to take all the six core units: STA201,STA204,STA221,STA222,STA223 and STA224, plus the following mathematics courses; SMA201,SMA203,SMA204,SMA205,SMA206 and SMA208.
3.7.    In the third year of study, a candidate is required to take all the ten core units; STA301,STA302,STA303,STA304,STA305,STA306,STA307,STA308,STA321 and STA322.
3.8.    In the fourth year of study, a candidate is required to take all the five core units: STA401,STA402,STA403,STA404 and STA420.
3.9.    In addition to the regulation above.
(i)    A candidate who specializes in Mathematical Statistics is required to take these five units STA406, STA407, STA408, STA410 and STA421.
(ii)    A Candidate who specializes in Economic Statistics is required to take these five units: STA410, STA421, STA422, STA432 and STA434.
(iii)    A candidate who specializes in Demography and Social Statistical is required to take these five units from: STA405,STA407,STA421,STA422 and STA434.
(iv)    A candidate who specializes in Biometry is required to take these five units: STA406, STA40, STA408, STA423 and STA437.

COURSE OUTLINE
Year I

Course Code	Course Title	Hours
Semester I (all core)
STA 103	Principles of Statistics	45
STA 121	Programming Methodology	45
SMA 101	Basic Mathematics	45
SMA 103	Calculus I	45
SMA 105	Geometry	45
CCS001	Communication Skills	45

 

Semester II (all core)

STA 101	Introduction to Probability and Statistics	45
STA 122	Computation Methods and Data Analysis I	45
SMA 104	Calculus II	45
SMA 108	Discrete Mathematics I	45
CCS008	Elements of Philosophy	45
CCS010	HIV/AIDS	45

 

Year II

Course Code	Course Title	Hours
Semester 1 (all core)
STA 201	Probability and Statistics I	45
STA 221	Microeconomics	45
STA 223	Operation Research	45
SMA 201	Advanced Calculus	45
SMA 203	Linear Algebra I	45
SMA 205	Introduction to Algebra	45

 

Semester II (all core)

STA 204	Quality Control and Sampling Inspection	45
STA 222	Time Series Analysis I	45
STA 224	Computation Methods and Data Analysis II	45
SMA 204	Linear Algebra II	45
SMA 206	Introduction to Real Analysis	45
SMA 208	Ordinary Differential Equations I	45

 

Year III

Code	Title	Hours
Semester I (all core)
STA 301	Probability and Statistics II	45
STA 303	Theory of Estimation	45
STA 305	Probability Modelling	45
STA 307	Macroeconomics	45
STA 321	Stochastic Models in Operations Research	45

 

Semester II (all core)

STA 302	Linear Modeling	45
STA 304	Test of Hypotheses	45
STA 306	Time Series Analysis II	45
STA 308	Sample Surveys Theory and Method I	45
STA 322	Computation Methods and Data Analysis III	45

 

Year IV

Code	Title	Hours
Semester I (core units)
STA 401	Measure Probability and Integration	45
STA 402	Bayesian Inference and Decision Theory	45
STA 403	Non Parametric Methods	45
STA 404	Design and Analysis of Experiments I	45

 

Semester I (Elective units)

STA 405	Applied Demography	45
STA 421	Operations Research III	45
STA 423	Stochastic Models for Biological Processes	45
STA 437	Survival Analysis	45

Semester II (core units)

STA 404	Multivariate Statistical Methods	45
STA 420	Project in Statistics	45

 

Semester II (Elective units)

STA 406	Applied Stochastics Processes	45
STA 408	Design and Analysis of Experiments II	45
STA 410	Sample Surveys Theory and Method II	45
STA 422	Stochastic Models for Social Processes	45
STA 432	Econometric Models I	45
STA 434	Survey Research Methods	45