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JOHN CABOT UNIVERSITY
COURSE CODE: "MA 208-5"
COURSE NAME: "Statistics I"
SEMESTER & YEAR:
Fall 2023
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SYLLABUS
INSTRUCTOR:
Stefano Arnone
EMAIL: [email protected]
HOURS:
MW 6:00 - 7:15 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
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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.
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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.
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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.
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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 | | Other editions of the textbook are also acceptable. | | | |
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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 to homework problems will be uploaded. Students are encouraged to solve homework problems even though they are not graded. | Not graded |
First intermediate exam | This 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 exam | This 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) | | 40/100 |
Attendance and class participation | Attending class on a regular basis and participating to the discussion will be key factors in determining your attendance and participation grade. | 10/100 |
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-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 are expected to come to class on a regular basis and to sit exams in the classroom. Coming late to class or leaving early will be possible only with permission of the instructor.
Students who miss one or two classes 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.
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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 | Session Focus | Reading Assignment | Other Assignment | Meeting Place/Exam Dates |
Week 1 to week 3 | Chapter 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.
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Week 3 to week 5 | Chapter 4: Introduction to Probability (sections 4.1 to 4.4) | | See above. | |
Week 5 to week 8 | Chapter 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 9 to week 11 | Chapter 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: second intermediate exam (chapters 5 to 8) |
Week 12 and week 13 | Chapter 10: Statistical inference about means and proportions with two populations. Chapter 11: Inference about populations variances (section 11.1). Chapter 12: Tests of goodness of fit (case of a multinomial distribution) (section 12.1) | | See above. | |
Week 14 | Chapter 14: Simple Linear Regression (sections 14.1 to 14.4); course review | | See above. | |
Week 15 (exams' week) | | | | Final Exam COMPREHENSIVE. See University Schedule for date and time. |
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