JOHN CABOT UNIVERSITY COURSE CODE: "MA 208-1" COURSE NAME: "Statistics I" SEMESTER & YEAR: Spring 2020

SYLLABUS INSTRUCTOR: Ian Roberts EMAIL: [email protected] HOURS: TTH 8:30 AM 9:45 AM 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: 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: Following a brief introduction to the subject, both graphical and numerical techniques for representing data sets will be analyzed. Probability theory is discussed, using both discrete and continuous probability distribution, before moving on to analyze sampling distributions, point estimators and confidence intervals. The course then progresses to look at hypothesis tests, covering tests of the mean, proportion and variance, as well as the difference between these parameters, and Chi-squared goodness of fit tests. There will also be an introduction to simple linear regression.

LEARNING OUTCOMES: Upon successful completion of this course students will be able to:  - Use core statistics terminology  - Organize data using both numerical and graphical methods  - Use measures of central tendency and variability to summarize a data set  - Calculate probabilities of events explained by the normal and standard normal distribution using appropriate tables  - Estimate population parameters using confidence intervals  - Carry out tests of hypothesis about population parameters  - Perform simple linear regression

TEXTBOOK: Book Title Author Publisher ISBN number Library Call Number Comments Format Local Bookstore Online Purchase Statistics for Business and Economics (11th International Edition) Anderson, Sweeney, Williams Cengage Learning 10-0-324-78325-6

REQUIRED RESERVED READING: NONE RECOMMENDED RESERVED READING: NONE

GRADING POLICY -ASSESSMENT METHODS: Assignment Guidelines Weight Homework assignments Sets of questions from the course textbook 20% First test Since the course builds progressively on knowledge gained, three quizzes (rather than one midterm exam) are held to help ensure that students have achieved the level required to progress productively with the course. This first quiz will test knowledge of material covered up to this point only. 15% Second test Since the course builds progressively on knowledge gained, three quizzes (rather than one midterm exam) are held to help ensure that students have achieved the level required to progress productively with the course. This second quiz will test knowledge of material covered up to this point only. 15% Third test Since the course builds progressively on knowledge gained, three quizzes (rather than one midterm exam) are held to help ensure that students have achieved the level required to progress productively with the course. This third quiz will test knowledge of material covered up to this point only. 15% Final examination The final examination is comprehensive and will test students on all topics covered during the course. 35% -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. This type of work demonstrates the ability to critically evaluate concepts and theory and has an element of novelty and originality. There is clear evidence of a significant amount of reading beyond that required for the cours BThis is highly competent level of performance and directly addresses the question or problem raised.There is a demonstration of some ability to critically evaluatetheory and concepts and relate them to practice. Discussions reflect the student’s own arguments and are not simply a repetition of standard lecture andreference material. The work does not suffer from any major errors or omissions and provides evidence of reading beyond the required assignments. CThis is an acceptable level of performance and provides answers that are clear but limited, reflecting the information offered in the lectures and reference readings. DThis level of performances demonstrates that the student lacks a coherent grasp of the material.Important information is omitted and irrelevant points included.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 issues raised in the question. Most of the material in the answer is irrelevant. -ATTENDANCE REQUIREMENTS: Students should make their best efforts to attend all classes and to arrive on time. Students with three absences or fewer (for whatever reason) will have the opportunity to drop the lowest scoring test and make up the difference in the final exam.

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

Week  Day Date Description Reading Assignments 1 Tue 21/01/20 Introduction to statistics Chapter 1 Ex. 2 - 11 inclusive (pp. 21 - 23) Thu 23/01/20 Descriptive statistics - measures of location, variability and spread Chapter 3 Chapter 3: Ex. 5, 6, 16, 19, 24, 26 - 29, 35, 41, 47 2 Tue 28/01/20 Descriptive statistics - Chebyshev to grouped data Chapter 3 Chapter 3: Ex. 52, 53, 56, 57. Thu 30/01/20 Introduction to probability - counting rules Chapter 4 3 Tue 04/02/20 Introduction to probability - assigning probabilities Chapter 4 Chapter 4: 1, 2, 3, 6, 7, 11, 12, 19, 20 Thu 06/02/20 Introduction to probability - events and their probabilities Chapter 4 4 Tue 11/02/20 Introduction to probability - conditional probability Chapter 4 Chapter 4: 25, 28, 31, 34, 38, 55, 56 Thu 13/02/20 Test 1 Deadline for homework chs. 1, 3-4 5 Tue 18/02/20 Discrete probability distributions Chapter 5 Chapter 5: 10, 13, 17, 32, 37 Thu 20/02/20 Continuous probability distributions Chapter 6 6 Tue 25/02/20 Continuous probability distributions Chapter 6 Chapter 6: 2, 7, 9, 12, 14, 17, 23, 26, 29 Thu 27/02/20 Sampling, sampling distributions Chapter 7 7 Tue 03/03/20 Sampling, sampling distributions Chapter 7 Chapter 7: 18, 19, 20, 26, 29, 36, 46, 50 Thu 05/03/20 Test 2 Deadline for homework chs. 5-7 8 Tue 17/03/20 Interval estimation Chapter 8 Thu 19/03/20 Interval estimation Chapter 8 Chapter 8: 1, 2, 5, 10, 11, 13, 16, 21, 27, 28, 39, 41 9 Tue 24/03/20 Interval estimation Chapter 8 Thu 26/03/20 Hypothesis tests Chapter 9 Chapter 9: 3, 4, 7, 9, 12, 19 10 Tue 31/03/20 Hypothesis tests Chapter 9 Chapter 9: 22, 28, 32, 37, 38 Thu 02/04/20 Hypothesis tests Chapter 9 11 Tue 07/04/20 Inference about means and proportions with 2 populations Chapter 10 Chapter 10: 2, 4, 5, 10, 12, 16, 20, 24, 25, 28, 30 Thu 09/04/20 Test 3 Deadline for homework chs. 8-10 12 Tue 14/04/20 Inference about means and proportions with 2 populations Chapter 10 Thu 16/04/20 Tests of goodness of fit and independence Chapter 12 Ch. 12:  4, 8, 12, 16 13 Tue 21/04/20 Tests of goodness of fit and independence Chapter 12 Thu 23/04/20 Simple linear regression Chapter 14 Chapter 14: 2, 3, 4, 6, 15, 18, 19 14 Tue 28/04/20 Simple linear regression Chapter 14 Thu 30/04/20 Review