Data Analysis
Statistical Research
Data Visualization
Quantitative Analysis

Statistics

Extracting Insights from Data for Decision Making

Department of Statistics

School of Physical Sciences (SPS) • Federal University of Technology, Akure

Probability Theory Statistical Inference Data Analysis Experimental Design Statistical Computing Data Science

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 Packs

Second Semester

STA 122 CBE Past Questions

Computer-based examination past questions for STA 122.

Download

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

400 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 Resources

Research 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