| CODE | SOR0210 | ||||||||||||
| TITLE | Data Treatment and Probability | ||||||||||||
| UM LEVEL | 00 - Mod Pre-Tert, Foundation, Proficiency & DegreePlus | ||||||||||||
| MQF LEVEL | 4 | ||||||||||||
| ECTS CREDITS | 2 | ||||||||||||
| DEPARTMENT | Statistics and Operations Research | ||||||||||||
| DESCRIPTION | - Basic Ideas on Treatment of Data - Types of Data - Data collection - Coding and Sorting of Data - Presentation of Data - Descriptive Statistics - Frequency Tables and Percentiles - Measures of Central Tendency - Measures of Dispersion - Elementary Probability - Permutations and Combinations - Venn Diagrams and Simple Applications - Addition and Multiplication Rules - Conditional Probability - Mutually Exclusive and Independent Events - Probability Distributions - Discrete Distributions: Uniform, Poisson, Binomial - Continuous Distributions: Exponential, Normal - Means, Variances and Standard deviations of these distributions Study-Unit Aims: The aims of this study-unit are to: - Discriminate between two selection methods (with and without replacement) and familiarize with different types of enumeration (multiplication rule, combinations and permutations); - Describe the properties of probability and use probability theory to solve problems for mutually exclusive events, independent events and conditional events; - Discriminate between discrete and continuous random variables and compute their expected value and variance; - Discriminate between different discrete distributions (Binomial and Poisson) and use these distributions to calculate the probabilities of discrete-type of random variables; - Discriminate between different continuous distributions (Exponential and Normal) and use these distributions to calculate the probabilities of continuous-type of random variables. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Understand the fundamental concepts of enumerative combinatorics (combinations and permutations) and analytic combinatorics (probability theory); - Familiarize with the concepts of expectation and variation and use these statistical tools to estimate the mean and variance of discrete and continuous random variables; - Discriminate between different types of discrete and continuous distributions and use these distributions to compute the probabilities of events. 2. Skills: By the end of the study-unit the student will be able to: - Solve real life problems related to combinatorics and probability; - Identify the appropriate distribution of specific discrete and continuous variables and use the properties of these distributions to solve probability problems; - Use computer software, particularly EXCEL and SPSS, to carry out Descriptive Statistics and compute the probabilities of events for specific distributions, including the Binomial, Poisson, Exponential and Normal distribution. Suitable arrangements will be made for time and space to be allocated to the instruction and use in practice of elementary modules in statistical software, time and human resources permitting. The package/s, which will be used, would preferably form part of some widely used software like readily available spreadsheet applications. Main Text/s and any supplementary readings: Main Texts: - McClave J, Sincich T,. A first Course in Statistics (2018) - 12th Edition, Pearson. ISBN 13: 978-1-292-16541-7 - Miller, I and Miller, M (2014) John E. Freund's Mathematical Statistics with Applications (Classic Version) (Pearson Modern Classics for Advanced Statistics Series) 8th Edition, Pearson Education Ltd. - Aho, K.A. (2013) Foundational and Applied Statistics for Biologists Using R 1st Edition. Taylor and Francis Group LLC. - Ross, Sheldon M. (2005) Introductory Statistics – Second Edition, Academic Press. Supplementary Readings: - Agresti A, Franklin C, Klingenberg B,. Statistics - The Art and Science of Learning from Data (2017) - 4th Edition, Pearson ISBN 13: 978-0-321-99783-8. - Hogg R.V, Tanis E.A, Zimmerman D. L,. Probability and Statistical Inference (2015) - 9th Edition, Pearson. ISBN 13: 978-1-292 -06235-8. |
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| STUDY-UNIT TYPE | Lecture | ||||||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Aiden Grech Emma Scicluna Kurt Dylan Buttigieg Karl Lewis Nicole Borg Derya Karagoz Lynsey Schembri |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years. |
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