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The Higher Canadian Institute for Business and Engineering Technology Quality Assurance Unit Course Specification Course Title: Introduction to Statistics Course Code: BADM 103 I. Basic Course Information Program(s) on which the course is given: Business Administration Core or Elective element of program Core course: Department offering the course: Business Academic level: First Semester in which course is offered: Fall Semester Course pre-requisite(s): none Credit Hours:3.00 Contact Hours Through: Lecture 3.0 Tutorial* 2.0 Practical* 0.0 Total 5.0 Approval date of course specification: September 2013 II. Overall Aims of Course This course provides an insight of the basic techniques of descriptive statistics insight of basic concepts and definitions as well as the typology of data sources and classification. It also developes an understanding of the data listing techniques, grouping and data description through measures of location and variation. The course focuses on the following topics: Probability concepts and probability distributions. III. Program ILOs covered by course Program Intended Learning Outcomes (By Code) Knowledge & Intellectual Skills Professional Skills Understanding K2,K10 I1,I4,I6 P4, P6,P9 General Skills G5 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 Upon Completion of the course, students should be able to: K.1 Distinguish between key definitions: population vs. sample, primary vs. secondary data types, qualitative vs. quantitative data, and time series vs. crosssectional data K.2 State the difference between descriptive and inferential statistics K.3 State the differences and similarities between different sampling methods K.4 Discuss how to categorize data by type and level of measurement K.5 Distinguish between different techniques for describing and displaying data numerically and graphically K.6 Distinguish between different statistical measures: central tendency, dispersion, location, and others K.7 Discuss different approaches to assessing probabilities b. Intellectual/Cognitive Skills Upon Completion of the course, students should be able to: I.1 Interpret data presented in frequency distributions or graphically I.2 Compute and interpret different central tendency measures, dispersion measures, measures of location, and other measures such as the coefficient of variation, and skewness I.3 Use numerical measures along with graphs, charts, and tables to describe data I.4 Apply common rules of probability c. Practical/Professional Skills Upon Completion of the course, students should be able to: P.1 Construct and interpret tabular and graphical data representations: frequency distribution, histogram, bar charts, pie charts, line charts, scatter diagrams, and stem-and-leaf diagrams P.2 Apply different statistical measures to real-life problems P.3 Construct and interpret a box and whisker graph P.4 Apply probability to business decision-making situations d. General and Transferable Skills Upon Completion of the course, students should be able to: G.1 Demonstrate necessary skills in time management, organization practices. G.2 Identify, and present the numerical dimensions of a problem G.3 Demonstrate problem solving skills 2 The Higher Canadian Institute for Business and Engineering Technology Quality Assurance Unit Course Specification V. Course Matrix Contents 1- Course ILOs Covered by Topic (By ILO Code) K&U I.S. P.S. G.S. Main Topics / Chapters Duration (Weeks) The (Where, Why, and How of ) Data Collection 1 K1,K2,K3 K4 I3 P2 3 K5 I1,I3 P1,P2 5 K5, K6 I1,I2 P2,P3 3 K7 I4 P2,P4 Graphs, Charts, and Tables– Describing Your Data Describing Data Using 3Numerical Measures Using Probability and 4Probability Distributions Net Teaching Weeks 2- G1-G2G3 G1-G2G3 G1-G2G3 G1-G2G3 12 VI. Course Weekly Detailed Topics / hours / ILOs Week No. 1 2 3 4 5 6 7 8 9 10 Sub-Topics Total Hours What is statistics? Tools for collecting data/ 3 Populations, samples, and sampling Data types & measurement level 5 Describing Data (Graphically & Tables) Frequency distributions & histograms 5 Describing Data (Graphically & Tables) Bar charts, pie charts, & stem leaf 5 Line charts & scatter diagrams Describing Data (Numerically) Central Tendency Measures (Mean, 5 Mode) Describing Data (Numerically) Central Tendency Measures (Median, 5 Weighted Mean) Midterm Exam Describing Data (Numerically) Dispersion Measures (Range and Mean 5 Deviation ) Describing Data (Numerically) Dispersion Measures (Variance and 5 Standard Deviation) Describing Data (Numerically) Location Measures (Percentiles, Quartiles), Interquartile range, Box and 5 whisker plot Other Measures (Skewness and coefficient of variation) Contact Hours Theoretical Practical Hours Hours* 3 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 The Higher Canadian Institute for Business and Engineering Technology Quality Assurance Unit Course Specification 11 12 13 14 15 Probability Basics of Probabilities (Events & sample 5 space, tree diagrams, mutually exclusive) Methods of Assigning Probability Probability Probability Rules (Addition rule, 5 Complement rule) Conditional Probability 5 Revision 5 Final Exam Total Teaching Hours 63 3 2 3 2 3 3 2 2 Teaching/Learning Method Lectures & Seminars Tutorials Computer lab Sessions Practical lab Work Reading Materials Web-site Searches Research & Reporting Problem Solving / Problem-based Learning Projects Independent Work Group Work Case Studies Presentations Simulation Analysis Selected Method VII. Teaching and Learning Methods Course ILOs Covered by Method (By ILO Code) K&U All All Intellectual Skills All All Professional Skills All All General Skills All All Others (Specify): 4 The Higher Canadian Institute for Business and Engineering Technology Quality Assurance Unit Course Specification 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. Midterm Exam Final Exam Quizzes Course Work Report Writing Case Study Analysis Oral Presentations Practical Group Project Individual Project Others (Specify): G.S. Assessment Week Weight / No. Percentage K1,K2,K3,K4,K5 K6 I1,I2,I3 P1,P2,P3 All 20% 7 All K1,K2,K3,K4,K5,K6 All I1,I2,I3 All P1,P2,P3 All All 50% 10% All All All All 20% 15 5,11 All Term IX. List of References Required Text Books David F. Groebner, P. W. Business Statistics a Decision-Making Approach: Mathxl. Pearson College Division, 2010. Course notes Recommended books Title: Probability and Mathematical Statistics Author: Shelden M.Ross, Edition: First Edition (Academic Press) Title: Statistical Thinking for Managers Author: Hildebrand/Ott , Edition: Fourth Edition Periodicals, Web sites, etc … X. Facilities required for teaching and learning Teaching aids Computer aided data show White boards Course coordinator: Dr. Ihab el Khodary Head of Department: Dr. Dina Krema Date: September 2013 5