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JOHN CABOT UNIVERSITY
COURSE CODE: "MA 209"
COURSE NAME: "Statistics II"
SEMESTER & YEAR:
Spring 2015
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SYLLABUS
INSTRUCTOR:
Majlinda Joxhe
EMAIL: [email protected]
HOURS:
MW 4:30 PM 5:45 PM
TOTAL NO. OF CONTACT HOURS:
45
CREDITS:
PREREQUISITES:
Prerequisites: MA 208 with a grade of C- or above; Co-requisite: CS 110 OR CS 160
OFFICE HOURS:
Every Wednesday from 3.00 p.m-4.00.pm or by appointment. To make an appointment, just approach me in class or send me an email. Please try to send e-mails ahead of time as I may not be able to accommodate last-minute and short-notice requests for an appointment. I will do my best to set up specific office hours before each exam.
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COURSE DESCRIPTION:
Continuing from the first course in statistcs, this course includes more advanced hypothesis testing, analysis of variance, regression analysis, and time series analysis
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SUMMARY OF COURSE CONTENT:
Review of hypothesis testing.
Statistial Inferences of means, proportions, and variances of two populations.
Tests of goodness of fit and independence.
Analysis of variance and experimental design.
Simple linear regression.
Multiple regression.
Regression analysis and model building.
Basic time series analysis and forecasting.
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LEARNING OUTCOMES:
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LEARNING OUTCOMES:
Students will learn how to use and apply statistics tools analytically. In particular, the students upon successful completion of this course students will be able to show:
1. a basic understanding of the theoretical framework for statistical inference;
2. an ability to undertake basic quantitative investigation and demonstrate application of the material covered in the course;
3. professionalism in presentation of quantitative information;
4. competency in using statistical software such as Microsoft Excel.
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TEXTBOOK:
| Book Title | Author | Publisher | ISBN number | Library Call Number | Comments | Format | Local Bookstore | Online Purchase |
| Statistics for Business and Economics (11th international edition | Anderson, Sweeney, Williams | CENGAGE Learning | 978-0-538-47188-6 | | Older editions of the same textbook are accepted. From one edition to the next, the changes are minimal, just a little difference in formatting and some of the exercises. Students are expected to solve the exercises in the 11th international edition | | | |
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REQUIRED RESERVED READING:
RECOMMENDED RESERVED READING:
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GRADING POLICY
-ASSESSMENT METHODS:
| Assignment | Guidelines | Weight |
| Homework | Homework assignments will be graded: the average grade weighs 10 percent of the final grade | 10% |
| Attendance | Full credit for attendance will be given to students with three or fewer unexcused absences. Four or more absences will result in a proportional reduction of the grade. | 10% |
| Midterm 1 | | 20% |
| Midterm 2 | | 20% |
| Project presentation | I will divide you on working groups (3 o 4 each) to work on a project presentation. Guidelines will be given during the classes. You will use the statistical tools covers during the lectures and dataset from some important economic site like IMF or World Bank. I will grade each group by giving 0-100 points. The points taken by the group will be the same for each student and will be weighed to your final mark by 10%. | 10% |
| Final exam (comprehensive) | | 30% |
-ASSESSMENT CRITERIA:
AWork of this quality directly addresses the question or problem raised and provides a coherent argument displaying an extensive knowledge of relevant information or content. This type of work demonstrates the ability to critically evaluate concepts and theory and has an element of novelty and originality. There is clear evidence of a significant amount of reading beyond that required for the cour
BThis is highly competent level of performance and directly addresses the question or problem raised.There is a demonstration of some ability to critically evaluatetheory and concepts and relate them to practice. Discussions reflect the student’s own arguments and are not simply a repetition of standard lecture andreference material. The work does not suffer from any major errors or omissions and provides evidence of reading beyond the required assignments.
CThis is an acceptable level of performance and provides answers that are clear but limited, reflecting the information offered in the lectures and reference readings.
DThis level of performances demonstrates that the student lacks a coherent grasp of the material.Important information is omitted and irrelevant points included.In effect, the student has barely done enough to persuade the instructor that s/he should not fail.
FThis work fails to show any knowledge or understanding of the issues raised in the question. Most of the material in the answer is irrelevant.
-ATTENDANCE REQUIREMENTS:
Full credit for attendance will be given to students with three or fewer unexcused absences. Four or more absences will result in a proportional reduction of the grade. Coming late to class or leaving early will be possible only with permission of the instructor.
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ACADEMIC HONESTY
As stated in the university catalog, any student who commits an act of academic
dishonesty will receive a failing grade on the work in which the dishonesty occurred.
In addition, acts of academic dishonesty, irrespective of the weight of the assignment,
may result in the student receiving a failing grade in the course. Instances of
academic dishonesty will be reported to the Dean of Academic Affairs. A student
who is reported twice for academic dishonesty is subject to summary dismissal from
the University. In such a case, the Academic Council will then make a recommendation
to the President, who will make the final decision.
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STUDENTS WITH LEARNING OR OTHER DISABILITIES
John Cabot University does not discriminate on the basis of disability or handicap.
Students with approved accommodations must inform their professors at the beginning
of the term. Please see the website for the complete policy.
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SCHEDULE
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Session
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Session Focus
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Chapters in the book
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Meeting Place/Exam Dates
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Week 1
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Review of hypothesis testing
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Chapter 9
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Week 2
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Review of statistical inference about means and proportions with two populations
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Chapter 10
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Week 3
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Inferences about population variances. Review of tests of goodness of fit and independence
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Chapter 11, 12
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Week 4 to 7
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Analysis of variance and experimental design. Simple linear regression
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Chapter 13, 14
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First Midterm exam on Week 7
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Week 8 to 9
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Multiple regression
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Chapter 15
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Week 10 to 11
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Regression analysis and model building
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Chapter 16
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Second Midterm exam on Week 10
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Week 12 to 13
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Forecasting
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Chapter 18
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Week 14
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Course review.
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Final exam (comprehensive) : see University schedule for date and time.
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