Department of Statistics
School of Physical Sciences (SPS) • Federal University of Technology, Akure
About the Department
The Department of Statistics at the Federal University of Technology, Akure (FUTA), within the School of Physical Sciences, is dedicated to developing competent statisticians and data professionals capable of collecting, analyzing, and interpreting data to support evidence-based decision-making. Our department trains graduates with expertise in statistical methods, probability theory, and computational techniques applicable across diverse sectors.
Statistics is the science of developing and applying methods for collecting, analyzing, and interpreting data such that conclusions can be assessed by means of logical reasoning based on probability. Our comprehensive curriculum integrates probability theory and stochastic processes, statistical inference and hypothesis testing, design of experiments and surveys, sampling techniques and theory, regression analysis and multivariate methods, quality control and operations research, statistical computing and data science, and applied statistics in various fields. Students develop expertise in statistical modeling, data manipulation, hypothesis testing, experimental design, and using statistical software.
The department features modern computing laboratories equipped with statistical software including R, Python, SAS, SPSS, Minitab, and Excel. Our curriculum aligns with international standards in statistical science and data analytics. We maintain active collaborations with government agencies, industries, research institutions, and financial organizations, providing students with opportunities to apply statistical methods to real-world problems through internships and consulting projects.
Graduates of Statistics are highly sought-after professionals in government, finance, healthcare, agriculture, manufacturing, education, and research sectors. They work as statisticians, data analysts, data scientists, research scientists, quality control specialists, and consultants. Our alumni successfully design studies, analyze complex datasets, build predictive models, and provide insights that drive organizational decisions both nationally and internationally.
What We Offer
Academic Programs
- B.Sc in Statistics - 4-year undergraduate program
- B.Sc in Statistics/Mathematics - Joint 4-year program
- B.Sc in Statistics/Economics - Joint 4-year program
- M.Sc in Statistics - Postgraduate degree
- Ph.D in Statistics - Advanced research degree
Core Focus Areas
- Probability Theory & Stochastic Processes
- Statistical Inference & Hypothesis Testing
- Design of Experiments & Surveys
- Sampling Techniques & Theory
- Regression Analysis & Multivariate Methods
- Quality Control & Operations Research
- Statistical Computing & Data Science
- Applied Statistics in Various Fields
Facilities & Resources
Computing Laboratory
R, Python, SAS, SPSS, Minitab software
Data Analysis Lab
High-performance systems for statistical analysis
Visualization Suite
Data visualization and graphics tools
Research Focus Areas
Our department conducts research across critical statistical and data science disciplines:
Probability Theory & Stochastic Processes
Probability axioms, distributions, moment generating functions, Markov chains, random walks, Brownian motion.
Statistical Inference & Hypothesis Testing
Point and interval estimation, confidence intervals, hypothesis testing, parametric and non-parametric tests, Bayesian inference.
Design of Experiments & Surveys
Experimental designs, ANOVA, factorial designs, randomized designs, survey design and methodology, questionnaire design.
Sampling Techniques & Theory
Simple random sampling, stratified sampling, cluster sampling, quota sampling, systematic sampling, sampling distributions.
Regression Analysis & Multivariate Methods
Linear regression, multiple regression, logistic regression, principal component analysis, cluster analysis, discriminant analysis.
Quality Control & Operations Research
Statistical process control, control charts, acceptance sampling, linear programming, network analysis, inventory management.
Statistical Computing & Data Science
Statistical software programming, data manipulation, visualization, machine learning, big data analytics, predictive modeling.
Applied Statistics in Various Fields
Biostatistics, econometrics, environmental statistics, social statistics, medical statistics, agricultural statistics.
Career Opportunities
Statistics graduates pursue diverse careers across sectors:
Data Analyst
Analyze data and provide insights
Data Scientist
Build predictive models with ML
Biostatistician
Apply statistics in health research
Research Scientist
Conduct statistical research
Business Analyst
Analyze business data
Clinical Statistician
Design clinical trials
Quality Analyst
Monitor quality metrics
Risk Analyst
Assess financial risks
Educator
Teach statistics
Course Materials & Resources
Access comprehensive statistics materials, datasets, software guides, and resources organized by academic level.
100 Level Resources - Introductory Statistics
Foundation courses in basic statistics and probability, including past questions.
First Semester
All Materials Available Offline
All 100 Level first semester STA materials are fully available in our offline study packs.
Access Offline Study PacksSecond Semester
200 Level Resources - Intermediate Statistics
Statistical inference, large sample distributions, probability theory, and related topics.
First Semester - STA 201 & 203
STA 200 Level Past Questions
Comprehensive past questions for 200 Level statistics courses
DownloadSTA 201 Lecture Manual
Complete lecture manual for STA 201
DownloadSTA 203 Handout (Large Samples Distribution)
Handout on large sample distributions for STA 203
DownloadBeginning Statistics
Introductory statistics textbook and notes
DownloadSecond Semester - STA 122 Reference
300 Level Resources - Advanced Statistics
Advanced statistical methods, distributions, assignments, and summaries.
First Semester Materials Coming Soon
300 Level first semester STA resources are being prepared.
Second Semester - STA 302
STA 302 Assignment Questions
Assignment questions for STA 302
DownloadSTA 302 Distribution Summary
Summary of statistical distributions for STA 302
DownloadSTA 302 Note
Comprehensive lecture notes for STA 302
DownloadSTA 302
General materials for STA 302
DownloadSTA 302 Questions
Practice questions for STA 302
Download400 Level Resources - Specialization & Research
Final year project, specialized topics, and advanced applications.
Research & Specialization
Final year project, quality control, operations research, advanced computing.
Access 400 Level ResourcesResearch Project
Original investigation and thesis
Quality Control
Advanced QC methods and practice
Operations Research
OR techniques and applications
Advanced Computing
Statistical programming, ML basics
Specialized Electives
Biostatistics, econometrics, etc.
Professional Practice
Career prep, professional standards
Admission Requirements
UTME Requirements
- Minimum UTME score as set by JAMB and FUTA
- Subject combination: English Language, Mathematics, and Physics
- Five O'Level credit passes in no more than two sittings
- O'Level credits must include: English, Mathematics, Physics, and two other subjects
Direct Entry Requirements (200 Level)
- A'Level passes in Mathematics and Physics (minimum grade C)
- A'Level pass in Statistics (minimum grade C)
- ND Upper Credit in Statistics or related discipline
- Plus O'Level requirements as stated above