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JOHN CABOT UNIVERSITY
COURSE CODE: "MA 208"
COURSE NAME: "Statistics I"
SEMESTER & YEAR:
Summer Session II 2025
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SYLLABUS
INSTRUCTOR:
Ian Roberts
EMAIL: [email protected]
HOURS:
MTWTH 9:00 AM 10:50 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
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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:
Following a brief introduction to the subject, 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.
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LEARNING OUTCOMES:
Upon successful completion of this course students will be able to:
- Use core statistics terminology
- Organize data using numerical 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
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TEXTBOOK:
| Book Title | Author | Publisher | ISBN number | Library Call Number | Comments | Format | Local Bookstore | Online Purchase |
| Statistics for Business and Economics, 5th Edition | Anderson/Sweeney/Williams/Camm/Cochran/Freeman/Shoesmith | McGraw Hill | 9781473768451 | | | | | |
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REQUIRED RESERVED READING:
RECOMMENDED RESERVED READING:
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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.
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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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| Description |
Reading |
| Introduction to statistics |
Chapter 1 |
| Descriptive statistics - measures of location, variability and spread |
Chapter 3 |
| Descriptive statistics - Chebyshev to grouped data |
Chapter 3 |
| Introduction to probability - counting rules |
Chapter 4 |
| Introduction to probability - events and assigning probabilities |
Chapter 4 |
| Introduction to probability - conditional probability |
Chapter 4 |
| Discrete probability distributions I |
Chapter 5 |
| Discrete probability distributions II (binomial probabilities) |
Chapter 5 |
| Test 1 |
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| Continuous probability distributions |
Chapter 6 |
| Continuous probability distributions |
Chapter 6 |
| Sampling, sampling distributions |
Chapter 7 |
| Sampling, sampling distributions |
Chapter 7 |
| Interval estimation |
Chapter 8 |
| Test 2 |
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| Interval estimation |
Chapter 8 |
| Interval estimation |
Chapter 8 |
| Hypothesis tests |
Chapter 9 |
| Hypothesis tests |
Chapter 9 |
| Hypothesis tests |
Chapter 9 |
| Inference about means and proportions with 2 populations |
Chapter 10 |
| Inference about means and proportions with 2 populations |
Chapter 10 |
| Test 3 |
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| Tests of goodness of fit and independence |
Chapter 12 |
| Tests of goodness of fit and independence |
Chapter 12 |
| Simple linear regression |
Chapter 14 |
| Simple linear regression |
Chapter 14 |
| Review |
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