Course Details

• Credit: 4
• Semester: 1
• Prerequisite: none
  

Synopsis

This course discusses on probability models for quality control of discrete random variation: random variation, cumulative distribution function, mean, variance and standard deviation. The course also discusses Discrete distribution: hypergeometrik distribution, Binomial distribution, Poisson distribution, Continuous distribution, Normal distribution, exponential distribution and uses in reliability modelling.

Course Objective

This course aims to introduce the fundamental statistical concepts and procedures. It also aims to introduce the use of varies statistical tests using computer applications.

Course Content

Lectures:
 ➤ Chapter 1: Probability and Statistics
 ➤ Chapter 2: Frequency Distribution and Graph
 ➤ Chapter 3: Data Description
 ➤ Chapter 4: Probability and Counter Tips
 ➤ Chapter 5: Discrete Probability Distribution
 ➤ Chapter 6: Normal Distribution
 ➤ Chapter 7: Confidence Interval and Sample Size
 ➤ Chapter 8: Hypothesis Testing
 ➤ Chapter 9: Difference Test between Two Mean, Two Variance and Two
 ➤ Chapter 10: Correlation and Regression
 ➤ Chapter 11: Variance Analysis
 ➤ Chapter 12: Non-parametric Statistics

Course Learning Outcomes

Upon successful completion of this course, students should be able to:
1. Show ability in using statistical techniques.
2. Explain analysis findings and statistical tests for obtaining alternative solutions.
3. Use statistical techniques for modelling and analysis.