Course Details
Course Information Package
Course Unit Title | PROBABILITY AND STATISTICS | ||||||
Course Unit Code | AMAT300 | ||||||
Course Unit Details | BSc Mechanical Engineering (Required Courses) - BSc Civil Engineering (Required Courses) - BSc Quantity Surveying (Required Courses) - | ||||||
Number of ECTS credits allocated | 5 | ||||||
Learning Outcomes of the course unit | By the end of the course, the students should be able to:
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Mode of Delivery | Face-to-face | ||||||
Prerequisites | AMAT122 | Co-requisites | NONE | ||||
Recommended optional program components | NONE | ||||||
Course Contents | Descriptive Statistics: Introduction to Statistics, Data Collection, Describing and Summarizing Data, Measures of Central Tendency, Dispersion and Skewness, Tables, Charts, Exploratory Data Analysis.
Probability: Sample Spaces and Events. Introduction to set theory and relations in set theory. Definitions of Probability and properties. Conditional probability.
Discrete Random Variables: Probability Distribution Function and cumulative distribution function, Mathematical Expectation, Mean and Variance. Probability Distributions: Binomial, Poisson.
Continuous Random Variables: Probability density Function and cumulative distribution function, Mathematical Expectation, Mean and Variance. Probability Distributions: Uniform, Normal Distribution. Approximations for Discrete Distributions.
Sampling distributions: Properties of sample distributions: Unbiasedness and minimum variance. The central limit theorem.
Estimation: Confidence Internal Estimation for Mean, Proportion, Difference of Means, Difference of Proportions. Sample size determination.
Hypothesis Testing: Hypothesis Testing for Mean, Proportion, Difference of Means, Difference of Proportions.
Introduction to regression: Simple Linear Regression and Correlation
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Recommended and/or required reading: | |||||||
Textbooks |
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References |
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Planned learning activities and teaching methods | The taught part of course is delivered to the students by means of lectures, conducted with the help of computer presentations. Lecture notes and presentations are available through the web for students to use in combination with the textbooks.
Several examples and exercises are solved in class to practice the theory and methodology taught. Students are then asked to work on their own during class hours on examples and practice problems. Extra assignments are given to students to tackle at home.
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Assessment methods and criteria |
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Language of instruction | English | ||||||
Work placement(s) | NO |