Course Syllabus

JOHN CABOT UNIVERSITY

COURSE CODE: "MA 209-2"
COURSE NAME: "Statistics II"
SEMESTER & YEAR: Spring 2022

SYLLABUS

INSTRUCTOR: Mary Merva
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: MW 6:00 to 6:45 pm by appointment

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.

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. It will also include discussions on interpretation of statistical information so as to uncover biases and hidden assumptions in the use of data. Students will make a presentation using statistical information.

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.

TEXTBOOK:

Book Title	Author	Publisher	ISBN number	Library Call Number	Comments	Format	Local Bookstore	Online Purchase
Statistics for Business & Economics, Revised 13e	Anderson, Sweeney, Williams et al	Cengage Learning	978-1337094160		Past editions of the textbook are also acceptable.

REQUIRED RESERVED READING:

NONE

RECOMMENDED RESERVED READING:

NONE

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%

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.

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.

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.

SCHEDULE

MA 209 Spring 2022 Weekly SCHEDULE

This schedule may be subject to changes.

Week 1: Jan. 17, 19

Review of hypothesis testing: statistical inferences about means and proportions with one and two populations and variances (chapter 9, 10)

Week 2: Jan. 24, 26

Review of hypothesis testing: statistical inferences about means and proportions with one and two populations and variances (chapter 9, 10)

Week 3: Jan. 31, Feb. 2

Inferences about population variances (chapter 11)

Week 4: Feb. 7, 9, 11

Review of tests of goodness of fit and independence (chapter 12)

Week 5: Feb. 14, 16, 18

Exam 1: Monday, February 14 Chapters 9, 10, 11, and 12.

Experimental Design and the Analysis of Variance (chapter 13)

Week 6: Feb. 21, 23

Simple linear regression (chapter 14)

Week 7: Feb. 28. Mar. 2

Simple linear regression (chapter 14)

Week 8: Mar. 7, 9

Exam 2: Monday, March 7, Chapters 13, 14

Week 9: Mar. 14, 16

Multiple regression (chapter 15)

Week 10: Mar. 28, 30

Multiple regression (chapter 15)

Regression analysis and model building (chapter 16).

Week 11: April 4, 6

Forecasting (chapter 17)

Exam 3: Wednesday, April 6, Chapters 15, 16

Week 12: April 11, 13

Sample Survey (chapter 22)

Week 13: April 20

Sample Survey (chapter 22 cont.)

Statistical Methods for Quality Control (chapter 19)

Week 14: April 27

Review

Week 15: Final Exam Period

Final exam comprehensive: Chapters 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 22

See University schedule for day and time.