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34 Courses Under Statistics Degree

On this article, I am going to list out all Statistics course outline in Nigeria Universities which you will study before you can to become a graduate of Statistics. Normally, a course outline should contain; course name, course description, course hours etc… but I am going to skip that information and go straight to Statistics subjects for university students.

I will only list out the course names excluding  GST Courses and those courses with part II and III to avoid too much information. There is no guarantee that the listed Statistics subjects (courses) will be fully covered in your school because universities in Nigeria does not use a uniform curriculum.

Nevertheless, you will study 97% of Statistics courses listed here.
The following Statistics courses in Nigeria listed here do not follow the traditional course structure and they have been arranged in alphabetical order. Notwithstanding, the list here covers 100 level courses, 200 level courses 300 courses and 400 level courses.
 

The following are the list of Statistics Courses in Nigeria

  • Actuarial Statistics
  • Bayesian Inference and Decision Theory
  • Biometric Methods
  • Demography
  • Design and Analysis of Experiments
  • Distribution Theory
  • Economics
  • Econometric Methods
  • Educational Statistics
  • Energy Statistics
  • Health Statistics
  • Inference
  • Introduction to Basic Programming
  • Introduction to Environmental Statistics
  • Introduction to Probability Theory
  • Introduction to Stochastic Processes
  • Linear Models
  • Logical Background of Statistics and Analysis of Theory
  • Medical Statistics
  • Multivariate Statistical Methods
  • Non-Parametric Methods
  • Operation Research
  • Probability and stochastic processes
  • Psychometric Methods
  • Regression Analysis
  • Sampling Techniques
  • Social and Economic Statistics
  • Statistical Computing
  • Statistical Inference
  • Statistical Quality Control
  • Statistics for Biological Science
  • Statistics for physical sciences and Engineering
  • Statistics for Social Sciences
  • Stochastic Processes
  • Survey Methods and Sampling Theory
  • Time-series Analysis

 
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