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JOHN CABOT UNIVERSITY

COURSE CODE: "MA 208-4"
COURSE NAME: "Statistics I"
SEMESTER & YEAR: Spring 2022
SYLLABUS

INSTRUCTOR: Stefano Arnone
EMAIL: [email protected]
HOURS: TTH 3:00 PM 4:15 PM
TOTAL NO. OF CONTACT HOURS: 45
CREDITS:
PREREQUISITES: Prerequisite: Placement into MA 197 or completion of MA 100 or MA 101 with a grade of C- or above
OFFICE HOURS: TTh 6:00 to 6:45 pm by appointment

COURSE DESCRIPTION:
An introduction to descriptive statistics, elementary probability theory and inferential statistics. Included are: mean, median, mode and standard deviation; probability distributions, binomial probabilities and the normal distribution; problems of estimation; hypothesis testing, and an introduction to simple linear regression.
SUMMARY OF COURSE CONTENT:

After a brief introduction to the subject, both graphical and numerical techniques for representing data sets will be analysed; probability theory will be then discussed using both discrete and continuous probability distributions. We will then move to analysing sampling distributions, point estimators and confidence intervals.

We will also discuss hypothesis tests covering tests of the mean, proportion, and variance as well as differences between these parameters, Chi-squared goodness of fit tests, and an introduction to simple linear regression.

LEARNING OUTCOMES:

Upon successful completion of this course students will be able to:

- Use statistical core terminology accurately.

- Organise data using both numerical and graphical methods.

- Use measures of central tendency and variability to summarise a data set.

- Calculate probabilities of events explained by the normal and the standard normal distribution using the appropriate tables.

- Estimate population parameters using confidence intervals.

- Carry out tests of hypothesis about population parameters.

TEXTBOOK:
Book TitleAuthorPublisherISBN numberLibrary Call NumberCommentsFormatLocal BookstoreOnline Purchase
Statistics for Business & Economics, Revised 13eAnderson, Sweeney, Williams et alCengage Learning978-1337094160 Other editions of the textbook are also acceptable.    
REQUIRED RESERVED READING:
NONE

RECOMMENDED RESERVED READING:
NONE
GRADING POLICY
-ASSESSMENT METHODS:
AssignmentGuidelinesWeight
HomeworkHomework assignments will be posted on Moodle; one week later solutions to homework problems will be uploaded. Students are encouraged to solve homework problems even though they are not graded. Not graded
First intermediate examThis grade could be substituted by the final exam grade if higher (see attendance requirements for details). The instructor reserves the right to ask students for clarification on any exercise on the exam to judge if the work they submitted is actually theirs.25/100
Second intermediate examThis grade could be substituted by the final exam grade if higher (see attendance requirements for details). The instructor reserves the right to ask students for clarification on any exercise on the exam to judge if the work they submitted is actually theirs.25/100
Final exam (comprehensive)The final exam may include or consist in a 10-minute group presentation, followed by questions from the instructor. Details will be given in class as the final exam nears.35/100
Attendance and class participation Once a week a new question will be posted on Moodle on the material that you are expected to have covered at the time of the post. Students are expected to answer all question posted. The average attendance-and-class-participation grade weighs 15 percent. NOTA BENE: each question that remains unanswered will receive a mark of 0 (zero), which will NOT be discarded when the average grade is computed. Once a new question is posted, answers to previous questions will not be taken into account. The first question will be posted at the beginning of the second week of classes.15/100

-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. 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.

-ATTENDANCE REQUIREMENTS:

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.

Students who maintain a class participation average of at least 80/100 (corresponding letter grade: B- or higher) will see the lower of their two intermediate exam grades substituted by the final exam grade if this latter is higher.

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 you 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.

The Instructor reserves the right to choose days and times for make-up exams that best fit his schedule, after consulting the student(s) involved.

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

SessionSession FocusReading AssignmentOther AssignmentMeeting Place/Exam Dates
Week 1 and week 2Chapter 1: Data and Statistics. Chapter 2: Descriptive statistics: tabular and graphical presentation. Chapter 3: Descriptive statistics: numerical measures. 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 3 to week 5Chapter 4: Introduction to Probability (sections 4.1 to 4.4)  See above. 
Week 5 to week 7Chapter 5: Discrete probability distributions: (sections 5.1 to 5.4). Chapter 6: Continuous probability distributions (sections 6.1 to 6.3)  See above.Week 7: first intermediate exam (chapters 1 to 4)
Week 8 to week 10Chapter 7: Sampling and Sampling Distributions (sections 7.1 to 7.7). Chapter 8: Interval Estimation. Chapter 9: Hypothesis Tests (sections 9.1 to 9.5)  See above. 
Week 11 and week 12Chapter 10: Statistical inference about means and proportions with two populations. Chapter 11: Inference about populations variances (section 11.1) See above.Week 11: second intermediate exam (chapters 5 to 8)
Week 12 and week 13Chapter 12: Tests of goodness of fit and independence (sections 12.1 and 12.2)  See above. 
Week 13 and week 14Chapter 14: Simple Linear Regression (sections 14.1 to 14.4)  See above. 
Week 14Course review  Final Exam COMPREHENSIVE. See University Schedule for date and time.