Doctor of Philosophy in Statistics

Philosophy of the Programme

The philosophy of this programme is to equip the students with analytic and research skills to enable them solve problems in the area of statistics and data analytics.

Rationale of the Programme

a) Needs assessment

The development of the Doctor of Philosophy in Statistics programme was informed by the outcome of a needs assessment carried out to establish the viability and areas of concern for the programme. The participants in the needs assessment included professionals in various fields such as local authorities, International Biometric Society, the health sector, the financial sector, academic staff and students from various institutions of higher learning. The views expressed by the various participants were that the program is in line with the economic and social pillar of Vision 2030. The programme has also been developed to accelerate the achievement of Sustainable Development Goals (SDGs) including poverty eradication (No. 1), elimination of hunger (No. 3), decent work and economic growth (No. 8). Thus, the programme will provide an opportunity to develop the requisite skills to teach and research in local and global institutions.

Specifically, the programme will enable the students demonstrate an ability to conduct original research with a depth of knowledge in the chosen area of specialization, design and execute competency in data analytics, demonstrate an understanding of the core principles of probability theory, optimal designs, and statistical methods, and critique statistical practices for ethical issues, including discriminatory practices, power imbalances, and invasions of privacy.

b) Stakeholders Involvement

Major stakeholders were involved to enrich the Doctor of Philosophy in statistics program. They included a representative from Kenya National Bureau of statistics, KEMRI, and KALRO. Others were lecturers from other universities, students, community representatives, and representatives from banks, insurance, KRA and other relevant industries. The views expressed by these stakeholders were that the curriculum should focus on intensive research aligned to the current issues in statistics such as data science and machine learning. This programme has responded to these concerns and it has included them in various course units, in particular, the stakeholders pointed out the need to align the curriculum to focus on professional ethics.

c) Justification of the Program

The Doctor of Philosophy in statistics program responds to the need to prepare professionals for leadership roles in statistics, data management and processing, training and research. From our analysis during needs assessment, there is an increasing demand for planners, analysts, technocrats, academicians, and researchers with knowledge in statistics. In Kenya, successful implementation of various projects requires advanced skills, knowledge and attitude in research for the growth of institutions of higher learning. Also advanced skills in Statistics is necessary to foster economic development, attainment of Vision 2030, SDGs, and the Africa 2063 Agenda.

Goal of the Programme

Doctor of Philosophy in Statistics aims to equip students with high level analytic, interpersonal and research skills. The program graduates are expected to demonstrate advanced research skills deeply grounded in statistics that complement their existing professional expertise.

Expected Learning Outcomes of the program

By the end of the programme, the student should be able to:

Demonstrate an ability to conduct independent, original research with a depth of knowledge in the chosen area of specialization.
Design and execute competency in data analytics.
Demonstrate an understanding of the core principles of probability theory, Optimal designs, and statistical methods.
Critique statistical practices for ethical issues, including discriminatory practices, power imbalances, and invasions of privacy.

Mode of delivery of the Program

The mode of study will be blended learning which will utilize both face-to-face interactions with an online learning component. Face to face consultations between supervisors and candidates during proposal development and writing thesis. It also includes presentations, seminars and workshops.

Academic regulations

Common Regulations for the Degree of Doctor of Philosophy (PhD) in all faculties shall be applicable.

Admission requirements

A candidate who wishes to be admitted to the program must have the minimum University general admissions requirements.

Holders of a Master of Science degree in Statistic of the University of Embu or any other institution recognized by the Senate.

Holders of Master’s Degree in areas of specialization relevant to the discipline of study in statistics from the University of Embu or any other institution recognized by the Senate.

Regulations on credit transfers

There is no provision for credit exemption under this program.

Regulation for Credit Transfer

There is no provision for credit transfer under this program.

Course Requirements

The program shall consist of two parts. In the first part, the students will register as a doctoral student where six course units shall be offered and examined. The Student is required to actively study the units under the guidance of a qualified lecturer. After successful completion of the first part, the student shall register as a doctoral candidate.

The doctoral programme shall consist of a minimum of six (6) semesters and a maximum of fifteen (15) semesters.
Registration as a Doctoral student:

For the purposes of eligibility for registration in the programme, an applicant who qualifies for admission into the course work phase shall be deemed to have satisfied the requirement spelt out in the common regulations for the degree of Doctor of Philosophy.
A successful applicant shall register as a doctoral student and take the required coursework. This student registration shall be for a minimum of two semesters and a maximum of six semesters. The student shall be required to complete the coursework phase and develop an acceptable research proposal before being enrolled as a doctoral candidate.
1. A student shall be required to take a total of six (6) course units in the programme.
2. A student is required to demonstrate that He/She has at least covered two thirds of the total number of lectures in a unit in order to be allowed to sit the end of semester examination in a given unit of the programme.
3. A lecturer shall ensure the programme course(s) are delivered in a manner that learning takes place in line with university requirements for teaching assessment and evaluation of a unit.
4. Each course (Except Independent Conceptual Study paper) shall be examined by a written paper lasting three hours at the end of each semester in which the course is given. The independent study paper shall be marked out of 100%. The pass mark for each course unit shall be fifty percent (50%). The final examination shall account for 60% of the marks in each taught unit while continuous assessment shall account for the remaining 40%.
5. Any student who fails to attain the pass mark in:
i) 50% or less of the units taken in an academic year shall be required to sit for a supplementary for the failed unit(s).
ii) Any supplementary examination shall be on recommendation of the School Board and approval by the Senate

iii) A student shall enroll as a doctoral candidate after fulfilling the following requirements.

iv) Successful completion of all six (6) courses units.
v) Presentation of an acceptable research proposal.
1. A candidate shall carry out supervised thesis research in the chosen area of specialization for a minimum period of four semesters and a maximum period of fifteen semesters, culminating in a doctoral thesis.
2. An extension of the registration period may be granted by the senate subject to satisfactory reasons being presented by the candidate.

Student Assessment Policy/Criteria

The course shall be evaluated in terms of units: a course unit being defined as a series of 45 one- hour lecture equivalents. For this purpose, one 1-hour lecture is equivalent to one 2-hour tutorial or one 3-hour practical or any combination of these that may be recommended by the School Board and approved by Senate.

All courses taken shall be examined during the semester in which they are offered. Such examination shall consist of continuous assessments tests and assignments where applicable, and end of semester examinations. End of semester examinations will comprise 60 percent of the total course marks whereas continuous assessment/practical’s and assignments, where applicable, will account for 40 percent. End of semester examinations will take three hours.

A candidate may, on the recommendation of the School Board of Examiners and approval by Senate, be admitted to Special Examinations, in the course(s) for which the candidate failed to sit Ordinary Examinations at the prescribed time. Special Examinations shall be graded as Ordinary Examinations.

Grading System

Each course shall be graded out of a maximum of 100 marks and the pass mark for each unit shall be 50 percent. Marks shall be translated into letter grades as follows:

70 – 100% A

60 – 69% B

50 – 59% C

49 % and below D (Fail)

Examination Regulations

The university examination policy shall apply. However, where there are grounds of examination irregularities the following shall apply:

The university shall regularly communicate the university examination rules and regulations to the students including the penalties associated with a breach of the same.
In all cases, a student shall be permitted to finish writing the examination. However, the invigilator must make a note of the time and details of the offence, including the level of cooperation from the student. This information should be filled in the relevant incident report

The invigilator shall explain to the student that the status of his/her examination is in question and set it aside.

All evidence and the incident report form shall be turned over to the Chairman of Department for onward transmission to the examinations office for necessary action.

Moderation of Examination

University examinations will be set by internal examiners and moderated at the departmental level. The moderated drafts shall be forwarded to the external examiner for moderation and returned to the department. Any suggestions by the external examiner shall be addressed and thereafter the department shall forward the moderated examination papers to the examination office.

The roles of the internal examiners are:

To ensure unit content is delivered adequately and resources availed to the learners.
To set examinations as per the course requirements.
To review and moderate departmental drafts examinations in relevant areas of specialization
To administer and process examinations as per the university examinations regulations
To address the concerns raised by the external examiners as per departmental approval.
To participate in Departmental and School Examinations Board meetings.

The roles of external examiners are:

To review and moderate draft examinations papers and any other form of assessment.
To evaluate structure, content and academic standards of a given teaching programme
To review and moderate end of semester’s summative results.
To evaluate and ensure consistency and fair distribution of marks in assessment process.

Graduation Requirement

To qualify for the award of a degree, a candidate for the Doctor of Philosophy in Statistics shall take a minimum of 6 units (270 lecture hours) during the first year of study. The candidate shall further be required to carry out supervised Thesis Research in his/her chosen area of study, for a minimum period of two years, culminating in a Doctoral Thesis.

Classification of Degrees

A Doctor of Philosophy in Statistics shall not be classified.

Thesis Examination

The research shall be examined by written thesis and oral presentation. Each student shall present at least four (4) seminars on the research proposal and thesis. Each candidate shall submit for examination a thesis, with the approval of the academic supervisors, at the end of the final semester. The thesis shall be examined in accordance with the common regulations of the Board of Postgraduate Studies of the University of Embu. A candidate who fails in the thesis examination may on the recommendation of the School Board of examiners be allowed to resubmit the thesis within 12 months up to a maximum of two times. A candidate, who fails after the second resubmission shall with the recommendation of the School Board and approval by senate, be discontinued.

Course Evaluation

The course will be subjected to an evaluation as per the Academic Quality Assurance Policy as shall be determined from time to time. The evaluation, as applicable, will cover the course content, instructional process, infrastructure and equipment for delivery, instructional and reference materials, and assessment.

Management and Administration of the Programme

The programme will be housed in the Department of Mathematics and Statistics. The chairman of the department shall oversee the management and administration of the programme in collaboration with dean of the school. An academic leader shall be responsible of students’ guidance in the programme. The academic leader will be at least in the rank of senior lecturer with an earned Doctorate degree in Statistics. Additionally, the program will be supported by a minimum of two full- time staff having doctorate degrees in Statistics or its equivalent. The program shall be subjected to internal quality assurance as determined by the University organs.

Course/Units Offered for the Programme

A distribution table of units per semester

The distribution of the courses per semester and academic year for the two academic year period shall be as shown in Table 1.

Table 1: Distribution of the courses per semester and academic year

S	Unit Code	Unit Name	Prerequisites	Contact Hours
YEAR 1 SEMESTER 1
	STA 801	Probability Theory and Stochastic Processes	None	45
	STA 803	Statistical Ethics and Professionalism	None	45
	STA 805	Optimal Designs and Mixtures	None	45
YEAR 1 SEMESTER 2
	STA 802	Research Methods	None	45
	STA 804	Seminars in Statistics	None	45
ELECTIVE COURSES
	STA 806	Data Mining and Machine Learning	None	45
	STA 808	Specialized Dimensional Methods	None	45
YEAR 2 AND YEAR 3
1.	STA 900	Thesis	STA 801, STA 802, STA 803, STA 804, STA 805, STA 806, STA 808	540

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