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The Higher Canadian Institute for Business and Engineering Technology Quality Assurance Unit Course Specification Course Name: Statistics and probability theory Course Code: BAS 212 I. Basic Course Information Program(s) on which the course is given: Engineering Common Course Department offering the course: Basic Science Department Academic level: 3rd level Semester in which course is offered: Fall Course pre-requisite(s): None Credit Hours: 3hrs Contact Hours Through: Lecture 2.0 Tutorial* 2.0 Practical* 0.0 Total 4.0 Approval date of course specification: September 2014 II. Overall Aims of Course To provide the student with a clear and detailed presentation of the statistics. Upon completion of this course, participants will be able to: Appreciate the value of exploratory methods in preliminary data analysis. Explore, characterize and identify problems and trends in data using graphical tools. Use descriptive statistics to summarize data. Master the concepts of hypothesis testing, confidence intervals, risk and power. Perform the appropriate statistical test based on the study objective. Analyze data more quickly and more accurately. Interpret results reliably and confidently III. Program ILOs covered by course Program Intended Learning Outcomes (By Code) Knowledge & Intellectual Skills Professional Skills Understanding K1, K5 I1, I3 P1, P6 General Skills G1, G6 1 The Higher Canadian Institute for Business and Engineering Technology Quality Assurance Unit Course Specification IV. Intended Learning Outcomes of Course (ILOs) a. Knowledge and Understanding On completing the course, students should be able to: k. 1 [Explain types of data and methods of presenting these data. k. 2 Discuss measures of tendency and dispersion. k. 3 State the different rules of probabilities. k. 4 Give practical examples of total probability and Bayes’ Rule. k. 5 Define the random variable and its related concepts such as probability distribution. k. 6 Recognize when to apply the uniform and exponential distributions. k. 7 Describe the characteristics of the normal distribution. k. 8 Translate normal distribution problems into standardized normal distribution problems. k. 9 Define the interval estimate of a parameter and confidence level of an interval estimate. k. 10 Explain the hypothesis testing.] b. Intellectual/Cognitive Skills: On completing the course, students should be able to i.1 Differentiate between different types of data. i.2 Construct an appropriate graph for a set of observed data. i.3 Evaluate the coefficient of correlation and coefficient of determination. i.4 Differentiate the different rules of probabilities. i.5 Formulate Engineering problems in mathematical model using random variables and random processes. i.6 Write an appropriate distribution for a set of observed data. i.7 Differentiate between different types of probability density function. c. Practical/Professional Skills On completing the course, students should be able to: p.1 Solve problems using the appropriate methods. p.2 Manipulate probability and random variables p.3 Employ probability methods in solving engineering problems p.4 Compute probabilities using a normal distribution table p.5 Compute the mean and standard deviation for a continuous probability distribution p.6 Prepare hypothesis testing and simple linear regression. d. General and Transferable Skills On completing the course, students should be able to g.1 React with each other through brain storming questions. g.2 Use the available resources effectively. V. Course Matrix Contents Main Topics / Chapters 1- Descriptive statistics 2- Probabilities Duratio n (Weeks) 3 3 Course ILOs Covered by Topic (By ILO Code) K&U I.S. P.S. G.S. k1, k2 i1, i2 p1 g1, g2 k3, k4 i4 p1, p3 g1, g2 2 The Higher Canadian Institute for Business and Engineering Technology Quality Assurance Unit Course Specification Random variables and probability distributions 4- Regression and correlation 5- Confidence intervals 6- Test of hypotheses 7Net Teaching Weeks 3- 3 1 1 1 k5, k6 , k7 , k8 p1, p2, p3, p4, p5 p6 i5, i6, i7 i3 k9 k10 p6 g1, g2 g1, g2 g1, g2 g1, g2 12 VI. Course Weekly Detailed Topics / hours / ILOs Week No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Total Hours Sub-Topics Types of data-Data Organization Presenting data Measures of Tendency Measures of dispersion Fundamentals of probability Counting rules Conditional probability Contact Hours Theoretical Practical Hours Hours* 2 2 4 2 2 4 4 4 4 Midterm Exam 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 26 24 [Characteristics of a probability 4 distributions and random variables ] Discrete random variable- Discrete 4] probability distributions Continues random variable- Continues 4 probability distributions Test of Hypotheses 4 Confidence interval 4 Simple Linear regression and correlation 4 coefficient Revision 4 Final Exam Total Teaching Hours 50 Teaching/Learning Method Lectures & Seminars Tutorials Computer lab Sessions Practical lab Work Reading Materials Web-site Searches Selected Method VII. Teaching and Learning Methods Course ILOs Covered by Method (By ILO Code) √ √ All All Intellectual Skills All All √ √ All All All All K&U Professional Skills All All General Skills All All All All g2 g2 3 The Higher Canadian Institute for Business and Engineering Technology Quality Assurance Unit Course Specification Research & Reporting Problem Solving / Problem-based Learning Projects Independent Work Group Work Case Studies Presentations Simulation Analysis √ All All All g2 Assessment Weight / Percentage Week No. Others (Specify): Selected Method VIII. Assessment Methods, Schedule and Grade Distribution Course ILOs Covered by Method (By ILO Code) Assessment Method K&U I.S. P.S. G.S. Midterm Exam √ Final Exam √ Quizzes √ Course Work Report Writing Case Study Analysis Oral Presentations Practical Group Project Individual Project √ k1, k2, k3 i1,i2, i3, i4 k4 All All k1, k2, i1, i2, i3 k3, k4, k5, i4, i5, i6, i7 , k6, k7, k8 All All p1, p2, p3 g2 20% 7 All g2 50% 15 10% 3, 5, 9 20% 2, …, 13 p1, p2, p3 p4, p5 All All Others (Specify): IX. List of References Essential Text Books Course notes Recommended books Statistics for Engineers and Scientists - Textbook ISBN #: 978-0-07-110222-3. Lecture Notes Daren S. Starnes, Dan Yates, David Moore, “The Practice of Statistics”, 4th edition, W. H. Freeman, 2010. John A. Gubner, “Probability and Random Processes for Electrical and Computer Engineers”, Cambridge University Press; 1st edition, ISBN: 978-0521864701, 2006. Oliver C. Ibe, “Fundamentals of Applied Probability and Random Processes”, Academic Press; 1st edition, ISBN: 978-0120885084, 2005. 4 The Higher Canadian Institute for Business and Engineering Technology Quality Assurance Unit Course Specification Richard H. Williams, “Probability, Statistics, and Random Processes for Engineers”, Cengage-Engineering; 1st edition, ISBN: 978-0534368883, 2002. Steven Kay, “Intuitive Probability and Random Processes using MATLAB”, Springer, 1st edition, ISBN: 978-0387241579, 2005. Periodicals, Web sites, etc … www.libgen.org X. Facilities required for teaching and learning Computer-Data show. Course coordinator: Dr. Hanaa Moussa Head of Department: Professor Dr. Refaat Salem Date: September 2014 5