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JOHN CABOT UNIVERSITY
COURSE CODE: "MA 209-2"
COURSE NAME: "Statistics II"
SEMESTER & YEAR:
Spring 2024
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SYLLABUS
INSTRUCTOR:
Mary Merva
EMAIL: [email protected]
HOURS:
MW 6:00 PM 7:15 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:
By appointment
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COURSE DESCRIPTION:
A continuation of Statistics I. Topics include more advanced hypothesis testing, regression analysis, analysis of variance, non-parametric tests, time series analysis and decision- making techniques.
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SUMMARY OF COURSE CONTENT:
This class will cover topics such as statistic inference and more advanced hypothesis testing, regression analysis, analysis of variance, non-parametric tests, time series analysis and decision- making techniques. Both Excel and STATA will be used. The course includes discussions on interpretation of statistical information so as to uncover biases and hidden assumptions in the use of data. Students will make written and oral presentations using statistical information. The ethics of how statistical information is used will be discussed.
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LEARNING OUTCOMES:
Upon successful completion of this course students will be able to show:
i. a basic understanding of the theoretical framework for statistical inference;
ii. an ability to undertake basic quantitative investigation and demonstrate application of the material covered in the course;
iii. professionalism in presentation of quantitative information;
iv. competency in using statistical software such as Microsoft Excel and STATA.
v. begin to understand the ethical issues with respect to the use of statistical information in decision-making.
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TEXTBOOK:
Book Title | Author | Publisher | ISBN number | Library Call Number | Comments | Format | Local Bookstore | Online Purchase |
Statistics for Business & Economics | D. Anderson, D. Sweeney, T. Williams, J. Freeman, E. Shoesmith | Cengage Learning | 9781473726567 | | Any previous edition of the Anderson Sweeney text will do. | | | |
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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 posted on Moodle; one week later, solutions will be uploaded. Students are encouraged to solve homework problems even though they will not be graded. | NOT GRADED |
First Test | Short problems. | 20% |
Second Test | Short problems. | 20% |
Third Test | Short problems. | 20% |
Statistics Presentation | Presentation and write up of a problem using statistics. To be assigned in class. | 10% |
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Final Exam | Comprehensive Final Exam | 30% |
-ASSESSMENT CRITERIA:
A Work of this quality directly addresses the question or problem raised and provides a coherent argument displaying an extensive knowledge of relevant information or content. The student demonstrates complete, accurate, and critical knowledge of all the topics, and is able to solve problems autonomously. 90-93 A- ; 94-100 A B This is highly competent level of performance and directly addresses the question or problem raised. There is a demonstration of some ability to critically evaluate theory and concepts and relate them to practice. The work does not suffer from any major errors or omissions and provides evidence that the student uses clear logic in his/her arguments. 80-83: B-; 84-86: B; 87-89 B9 C This is an acceptable level of performance and provides answers that are clear but limited, reflecting the information offered in the lectures. Mathematical statements are properly written most of the time. 65-69: C-; 70-75: C; 76-79: C+ D This level of performances demonstrates that the student lacks a coherent grasp of the material. Important information is omitted and irrelevant points included. Many mistakes are made in solving the problem raised. In effect, the student has barely done enough to persuade the instructor that s/he should not fail. 60-64: D+: 55-59: D: 50-54: D- F This work fails to show any knowledge or understanding of the subject-matter. Most of the material in the answer is irrelevant. Below 50: F
-ATTENDANCE REQUIREMENTS:
Students may have up to 4 absences for any reason. If you have not successfully petitioned to be a remote student, you can certainly join the class remotely, but, that will count as one of your absences.
Students who have 4 or fewer absences have the option of dropping their lowest midterm exam and moving the weight to the final exam which is comprehensive.
Students who are not taking the course fully remotely are expected to come to class on a regular basis and to sit exams in the classroom. Indeed, only those students who successfully petitioned for remote learning will be able to take exams remotely. Coming late to class or leaving early will be possible only with permission of the instructor.
Major exams cannot be made up without the permission of the Dean’s Office. Students who will be absent from a major exam must notify the Dean’s Office prior to that exam. Absences from class due to the observance of a religious holiday will normally be excused. Individual students who will have to miss class to observe a religious holiday should notify the instructor by the end of the Add/Drop period to make prior arrangements for making up any work that will be missed.
If you have an excuse from the Dean's Office for missing an exam, the weight of that exam will be placed on your final exam. You can obtain the exam missed and practice it but, make-up exams will not be given.
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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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MA 209 Spring 2023 Weekly SCHEDULE
This schedule may be subject to changes.
Week 1:
Review of hypothesis testing: statistical inferences about means and proportions with one and two populations and variances
Week 2:
Review of hypothesis testing: statistical inferences about means and proportions with one and two populations and variances
Week 3:
Review of tests of goodness of fit and independence
Experimental Design and the Analysis of Variance
Week 4:
Experimental Design and the Analysis of Variance
Week 5:
Exam 1: Wednesday
Week 6:
Simple linear regression
Week 7:
Simple linear regression
Week 8:
Exam 2: Wednesday
Week 9:
Multiple regression
Week 10:
Multiple regression
Regression analysis and model building
Week 11:
Forecasting
Exam 3: Wednesday
Week 12: April 11, 13
Sample Survey
Week 13: April 20
Sample Survey
Statistical Methods for Quality Control
Week 14: April 27
Review
Week 15: Final Exam Period
Final exam comprehensive
See University schedule for day and time.
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