
If you are planning to study Statistics and Data Science at Lead City University, Ibadan located in Oyo State, it is important to understand the admission requirements, cut-off mark, and career opportunities before applying. This page explains everything you need to know to increase your chances of gaining admission into Lead City University.
Does Lead City University, Ibadan (LCU) offer Statistics and Data Science?
No, Lead City University, Ibadan does not offer Statistics and Data Science under its Faculty of Data and Decision Sciences. However, since our course list is updated regularly, you can visit the courses available at Lead City University, Ibadan (LCU) below to check if the Statistics and Data Science course under the Faculty of Data and Decision Sciences has been updated.
Admission Requirements for Statistics and Data Science When Accredited in Lead City University, Ibadan (LCU)
O’Level Requirements
To study this course, candidates aspiring to gain admission into Statistics and Data Science department under Faculty of Data and Decision Sciences, should at least obtain five (5) credit (C5 and above) passes in their SSCE subjects including:
two (2) other relevant subjects.
JAMB Subject Combination
one (1) other relevant subjects.
Lead City University Cut-Off Mark for Statistics and Data Science
The general UTME cut-off mark is 180, but due to the variation of Statistics and Data Science cut-off mark depending on the admission year and competition level, we suggest you enquire about the recent JAMB UTME cut-off mark from Lead City University Officials. However, to improve your admission chances:
Perform well in Post-UTME screening.
Other Lead City University Science Courses with their Requirements
Nursing (Science)
SSCE Requirements
To study this course, the minimum requirement for applicants seeking admission to the Nursing (Science) department, is five (5) credits (C5 and higher) in their SSCE subjects, including the following:
Education and Mathematics
SSCE Requirements
To study this course, candidates seeking admission into the Education and Mathematics department, must have at least five (5) credits (C5 and more) in their SSCE disciplines, including the following:
one (1) other Science subject, and
any other relevant subjects.
Computer Science with Economics
SSCE Requirements
To study this course, candidates seeking admission into the Computer Science with Economics department, must have at least five (5) credits (C5 and more) in their SSCE disciplines, including the following:
two (2) other Science subjects.
Wood Production Engineering
SSCE Requirements
To study this course, the minimum requirement for applicants seeking admission to the Wood Production Engineering department, is five (5) credits (C5 and higher) in their SSCE subjects, including the following:
any other Science subject.
Information Technology
SSCE Requirements
To study this course, the minimum requirement for applicants seeking admission to the Information Technology department, is five (5) credits (C5 and higher) in their SSCE subjects, including the following:
any two (2) other relevant subjects.
Architecture
SSCE Requirements
To study this course, the minimum requirement for applicants seeking admission to the Architecture department, is five (5) credits (C5 and higher) in their SSCE subjects, including the following:
Fine Art, Geography or Wood Work, Biology, Economics, Technical Drawing, Further Mathematics, Introduction to Building Construction, Bricklaying / Block laying, Concreting, Wall,
Floors and Ceiling Finishing, Joinery, Carpentary, Decorative Painting, Lining, Sign and Design, Wall Hanging, Colour Mixing / Matching and Glazing, Ceramics, Graphics Design, Graphic Printing, and Basic Electricity
Mechanical Engineering
SSCE Requirements
To study this course, candidates seeking admission into the Mechanical Engineering department, must have at least five (5) credits (C5 and more) in their SSCE disciplines, including the following:
any two (2) other relevant Science subjects.
Nigerian Tertiary Institutions Offering Statistics and Data Science Course