Singapore University of Social Sciences

Fundamentals of Statistics and Probability (MTH219)

Applications Open: 01 October 2019

Applications Close: 30 November 2019

Next Available Intake: January 2020

Course Types: Modular Undergraduate Course

Language: English

Duration: 6 months

Fees: To be confirmed

Area of Interest: Science & Technology

Schemes: Lifelong Learning Credit (L2C)

Funding: To be confirmed


Students are exposed to the essential and important concepts of Statistics and Probability for data analysis. Illustrative examples in various discipline will be discussed. Emphssis will be on understanding data variability and uncertainty; cultivating statistical thinking and applying statistical techniques to solve real-life practical problems. Descriptive statistics and useful probability models will be introduced.

Level: 2
Credit Units: 5
Presentation Pattern: Every semester
E-Learning: BLENDED - Learning is done MAINLY online using interactive study materials in Canvas. Students receive guidance and support from online instructors via discussion forums and emails. This is supplemented with SOME face-to-face sessions. If the course has an exam component, this will be administered on-campus.


  • Exploring data.
  • Graphical displays.
  • Interpreting and analysing data.
  • Descriptive statistics, measures of location and dispersion.
  • Modelling variation.
  • Expectation and variance of random variables.
  • Probability models.
  • Bernoulli trials, binomial, geometric and uniform distributions.
  • Poisson approximation for rare events and exponential models.
  • Normal distribution.
  • Functions of random variables.

Learning Outcome

  • Describe the meaning of “Data".
  • Explain the roles of statistics and probability concepts in analyzing data.
  • Analyze data using appropriate probability models and statistical methods.
  • Identify the key features of data using appropriate descriptive statistics.
  • Apply the concepts of random variables and related properties.
  • Identify some useful continuous probability models.
  • Apply statistical techniques to practical problems and draw appropriate conclusions.
  • Discuss a number of probability models.
  • Solve models based on the normal distribution.
  • Apply a range of statistical techniques
  • Analyze and solve problems individually and/or as part of a group.
  • Solve a number of problems within strict deadlines.
  • Use R to solve and examine problems related to statistics and probability.
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