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COURSE NAME: "Statistics II"
SEMESTER & YEAR: Summer Session I 2020

INSTRUCTOR: Stefano Arnone
EMAIL: [email protected]
HOURS: Remote Learning
PREREQUISITES: Prerequisites: CS 110, MA 208 with a grade of C- or above

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.
Topics include:

review of hypothesis testing;

statistical 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.

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.

Book TitleAuthorPublisherISBN numberLibrary Call NumberComments
Statistics for Business & Economics, Revised 13eDavid R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. CochranCengage Learning 978-1337094160 Past editions of the textbook are also acceptable though (some of) the problems will be different from those from the current edition.

HomeworkHomework assignments will be posted on Moodle; on the due date, solutions to the problems will be uploaded. Students are encouraged to solve homework problems even though they are not graded.not graded
Attendance and class participationTwice a week a question will be posted on Moodle's Class Participation Forum; the question will be on the material that you are expected to have covered at the time of the post. Your answers will be graded: the average attendance-and-class-participation grade weighs 15 percent. In order to get a perfect score on attendance and class participation you must answer all questions posed correctly: each question that remains unanswered will cause your participation mark to decrease by 11 percent. Once a new question is posted, answers to previous questions will not be taken into account. [You are also encouraged to respond to your classmates'answers if you have some sort of feedback for them.]15%
First intermediate exam In order to ensure academic integrity of the online course, students may be asked to clarify and expand on the answers they provided to exam questions. 25%
Second intermediate exam In order to ensure academic integrity of the online course, students may be asked to clarify and expand on the answers they provided to exam questions. 25%
Final exam (comprehensive) In order to ensure academic integrity of the online course, students may be asked to clarify and expand on the answers they provided to exam questions. 35%

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. The student demonstrates complete, accurate, and critical knowledge of all the topics, and is able to solve problems autonomously.
BThis 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.
CThis 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.
DThis 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.
FThis work fails to show any knowledge or understanding of the subject-matter. Most of the material in the answer is irrelevant.


Full credit for attendance will be given to students with two or fewer unexcused absences. Three 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.

Major exams cannot be made up without the permission of the Dean’s Office. The Dean’s Office will grant such permission only when the absence was caused by a serious impediment, such as a documented illness, hospitalization or death in the immediate family (in which the student must attend the funeral) or other situations of similar gravity. Absences due to other meaningful conflicts, such as job interviews, family celebrations, travel difficulties, student misunderstandings or personal convenience, will not be excused. 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.

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.
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.


SessionSession FocusReading AssignmentOther AssignmentMeeting Place/Exam Dates
Week 1Review of hypothesis testing (chapter 9). Statistical inference about means and proportions with two populations (chapter 10). Inferences about population variances (chapter 11). Tests of goodness of fit and independence (chapter 12). Students may use the exercises at the end of each section of the textbook for extra practice, as needed. Depending on the edition, there might also be supplementary exercises at the end of each chapter.  
Week 2Experimental design and analysis of variance (chapter 13). See above 
Week 3Analysis of variance (cont.). Simple linear regression (chapter 14). Multiple regression (chapter 15). See aboveFirst intermediate exam at the beginning of week 3 (Monday, Jun 8th)
Week 4Multiple linear regression (cont.). Regression analysis and model building (chapter 16). See above 
Week 5Time series analysis and forecasting (chapter 17). Course review. See aboveSecon intermediate exam at the beginning of week 5 (Monday, June 22th)