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JOHN CABOT UNIVERSITY

COURSE CODE: "MA 208-1"
COURSE NAME: "Statistics I"
SEMESTER & YEAR: Fall 2019
SYLLABUS

INSTRUCTOR: Ian Roberts
EMAIL: [email protected]
HOURS: MW 8:30-9:45 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
TEXTBOOK:
Book TitleAuthorPublisherISBN numberLibrary Call NumberComments
Statistics for Business and Economics (11th International Edition)Anderson, Sweeny, williamsCengage Learning10 - 0-324-78325-6 or 13 - 978-0-324-78325  
REQUIRED RESERVED READING:
NONE

RECOMMENDED RESERVED READING:
NONE
GRADING POLICY
-ASSESSMENT METHODS:
AssignmentGuidelinesWeight
Homework assignmentsSets of questions from the course textbook20%
First testSince 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 testSince 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 testSince 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 examinationThe 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. Late arrivals in class will affect the participation grade. 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 Mon 02/09/19 Introduction to statistics Chapter 1 Ex. 2 - 11 inclusive (pp. 21 - 23)
Wed 04/09/19 Descriptive statistics - measures of location, variability and spread Chapter 3 Chapter 3: Ex. 5, 6, 16, 19, 24, 26 - 29, 35, 41, 47, 50 
2 Mon 09/09/19 Descriptive statistics - Chebyshev to grouped data Chapter 3 Chapter 3: Ex. 52, 53, 56, 57.
Wed 11/09/19 Introduction to probability - counting rules Chapter 4
3 Mon 16/09/19 Introduction to probability - assigning probabilities Chapter 4 Chapter 4: 1, 2, 3, 6, 7, 11, 12, 19, 20
Wed 18/09/19 Introduction to probability - events and their probabilities Chapter 4
4 Mon 23/09/19 Introduction to probability - conditional probability Chapter 4 Chapter 4: 25, 28, 31, 34, 38, 55, 56
Wed 25/09/19 Test 1 Deadline for homework chs. 1, 3-4
5 Mon 30/09/19 Discrete probability distributions Chapter 5 Chapter 5: 10, 13, 17, 32, 37
Wed 02/10/19 Continuous probability distributions Chapter 6
6 Mon 07/10/19 Continuous probability distributions Chapter 6 Chapter 6: 2, 7, 9, 12, 14, 17, 23, 26, 29
Wed 09/10/19 Sampling, sampling distributions Chapter 7
7 Mon 14/10/19 Sampling, sampling distributions Chapter 7 Chapter 7: 18, 19, 20, 26, 29, 36, 46, 50
Wed 16/10/19 Test 2 Deadline for homework chs. 5-7
8 Mon 21/10/19 Interval estimation Chapter 8
Wed 23/10/19 Interval estimation Chapter 8 Chapter 8: 1, 2, 5, 10, 11, 13, 16, 21, 27, 28, 39, 41
9 Mon 28/10/19 Interval estimation Chapter 8
Wed 30/10/19 Hypothesis tests Chapter 9 Chapter 9: 3, 4, 7, 9, 12, 19
10 Mon 04/11/19 Hypothesis tests Chapter 9 Chapter 9: 22, 28, 32, 37, 38
Wed 06/11/19 Hypothesis tests Chapter 9
11 Mon 11/11/19 Inference about means and proportions with 2 populations Chapter 10 Chapter 10: 2, 4, 5, 10, 12, 16, 20, 24, 25, 28, 30
Wed 13/11/19 Test 3 Deadline for homework chs. 8-10
12 Mon 18/11/19 Inference about means and proportions with 2 populations Chapter 10
Wed 20/11/19 Tests of goodness of fit and independence Chapter 12 Ch. 12:  4, 8, 12, 16
13 Mon 25/11/19 Tests of goodness of fit and independence Chapter 12
Wed 27/11/19 Simple linear regression Chapter 14 Chapter 14: 2, 3, 4, 6, 15, 18, 19
14 Mon 02/12/19 Simple linear regression Chapter 14
Wed 04/12/19 Review