

JOHN CABOT UNIVERSITY
COURSE CODE: "MA 2083"
COURSE NAME: "Statistics I"
SEMESTER & YEAR:
Fall 2017

SYLLABUS
INSTRUCTOR:
Ian Roberts
EMAIL: [email protected]
HOURS:
MW 11:3012:45 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:
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 Chisquared 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 Title  Author  Publisher  ISBN number  Library Call Number  Comments 
Statistics for Business and Economics, International Edition, 11th Edition  David R. Anderson; Dennis J. Sweeney; Thomas A. Williams  SouthWestern, Cengage Learning  ISBN10: 0538471883 ISBN13: 9780538471886   

REQUIRED RESERVED READING:
RECOMMENDED RESERVED READING:

GRADING POLICY
ASSESSMENT METHODS:
Assignment  Guidelines  Weight 
Homework assignments  Sets of questions from the course textbook  20% 
First quiz  Since the course builds progressively on knowledge gained, two 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.  20% 
Second quiz  Since the course builds progressively on knowledge gained, two 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 quizz will test knowledge of material covered up to this point only.  20% 
Final examination  The final examination is comprehensive and will test students on all topics covered during the course.  40% 
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 studentâ€™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 are allowed three absences during the semester for whatever reason. There is no need to justify these three absences and they will have no
effect on the final grade. Every additional absence after that, for whatever reason, will lower the student’s final grade by one grade level (e.g., a final grade of a B+ would be lowered to a B and so on).


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 
1 
Mon 
28/08/17 
Introduction to statistics 
Chapter 1 
Wed 
30/08/17 
Descriptive statistics  tabular and graphical presentation 
Chapter 2 
2 
Mon 
04/09/17 
Descriptive statistics  location, variability and spread 
Chapter 3 
Wed 
06/09/17 
Descriptive statistics  Chebyshev to grouped data 
Chapter 3 
3 
Mon 
11/09/17 
Introduction to probability  counting rules 
Chapter 4 
Wed 
13/09/17 
Introduction to probability  assigning probabilities 
Chapter 4 
4 
Mon 
18/09/17 
Introduction to probability  events and their probabilities 
Chapter 4 
Wed 
20/09/17 
Introduction to probability  conditional probability 
Chapter 4 
Fri 
22/09/17 
Review 

5 
Mon 
25/09/17 
Quiz 1 (chapters 1  4) 

Wed 
27/09/17 
Discrete probability distributions 
Chapter 5 
6 
Mon 
02/10/17 
Continuous probability distributions 
Chapter 6 
Wed 
04/10/17 
Continuous probability distributions 
Chapter 6 
7 
Mon 
09/10/17 
Sampling, sampling distributions 
Chapter 7 
Wed 
11/10/17 
Sampling, sampling distributions 
Chapter 7 
8 
Mon 
16/10/17 
Interval estimation 
Chapter 8 
Wed 
18/10/17 
Interval estimation 
Chapter 8 
9 
Mon 
23/10/17 
Review 

Wed 
25/10/17 
Quiz 2 (chapters 5  8) 

10 
Mon 
30/10/17 
Hypothesis tests 
Chapter 9 
11 
Mon 
06/11/17 
Hypothesis tests 
Chapter 9 
Wed 
08/11/17 
Inference about means and proportions with 2 populations 
Chapter 10 
12 
Mon 
13/11/17 
Inference about means and proportions with 2 populations 
Chapter 10 
Wed 
15/11/17 
Tests of goodness of fit and independence 
Chapter 12 
13 
Mon 
20/11/17 
Tests of goodness of fit and independence 
Chapter 12 
Wed 
22/11/17 
Simple linear regression 
Chapter 14 
14 
Mon 
27/11/17 
Simple linear regression 
Chapter 14 
Wed 
29/11/17 
Review 

15 

TBD 
FINAL EXAM (comprehensive) 


