Math 105002: Elementary Probability and Statistics
Spring 2019 Course Syllabus
NJIT Academic Integrity Code: All Students should be aware that the Department of Mathematical Sciences takes the University Code on Academic Integrity at NJIT very seriously and enforces it strictly. This means that there must not be any forms of plagiarism, i.e., copying of homework, class projects, or lab assignments, or any form of cheating in quizzes and exams. Under the University Code on Academic Integrity, students are obligated to report any such activities to the Instructor.
Course Information
Course Description: Consider notions of probability. Topics include the binomial and normal distributions, expected value, and variance. The notions of sampling, hypothesis testing, and confidence intervals are applied to elementary situations.
Number of Credits: 3
Prerequisites: None.
CourseSection and Instructors
CourseSection 
Instructor 
Math 105002 
Professor P. Natarajan 
Office Hours for All Math Instructors: Spring 2019 Office Hours and Emails
Required Textbook:
Title 
Introductory Statistics v1.0 
Author 
Douglas S. Shafer and Zhiyi Zhang 
Edition 
1st 
Publisher 
 
ISBN # 
9781453344873 
Other Textbook 
Statistics Using Technology by Kathryn Kozak, 2nd Ed. 
Reference Textbooks
 Openstax: Introductory Statistics
 Senior Contributing Author(s): Barbara Illowsky and Susan Dean
 Digital: ISBN10: 1947172050
 Inferential Statistics and Probability: A Holistic Approach
 Author: Maurice A. Geraghty
 OpenStax CNX: Collaborative Statistics Using Spreadsheets
 Authors: Susan Dean, Irene Mary Duranczyk, Barbara Illowsky, Suzanne Loch, Janet Stottlemyer
 OpenIntro Statistics 3rd edition
 Author: David M Diez, Christopher D Barr, and Mine CetinkayaRundel
Free PDF copies of the textbooks are available online. See course homepage on Canvas for details
Universitywide Withdrawal Date: The last day to withdraw with a W is Monday, April 8, 2019. It will be strictly enforced.
Course Goals
Course Objectives
 The objective of this course is to acquaint students with basic concepts and methods in statistics and probability and demonstrate real world applications using examples drawn from various fields. Topics to be covered include sampling, descriptive statistics, correlation and regression, notions of probability, binomial and normal distributions, estimation and hypothesis testing.
Course Outcomes: Upon successful completion of this course, the student will be able to 
 Demonstrate their understanding of various statistical terms, types of data, and data collection methods
 Efficiently summarize, organize, and present data
 Effectively compute measures of central tendency, position, and variation and interpret the results
 Demonstrate their understanding of notions of probability and distributions
 Perform statistical analysis, such as estimation, hypothesis testing, correlation and regression and draw conclusions
 Apply statistical reasoning to real world problems and make informed decisions
Course Assessment: The assessment tools used will include weekly homework assignments/quizzes, two midterm exams and a cumulative/comprehensive final exam.
Policies
DMS Course Policies: All DMS students must familiarize themselves with, and adhere to, the Department of Mathematical Sciences Course Policies, in addition to official universitywide policies. DMS takes these policies very seriously and enforces them strictly.
Grading Policy: The final grade in this course will be determined as follows:
Homework and Quizzes 
15% 
Midterm Exam I 
25% 
Midterm Exam II 
25% 
Final Exam 
35% 
Your final letter grade will be based on the following tentative curve.
A 
90  100 
C 
65  74 
B+ 
85  89 
D 
55  64 
B 
80  84 
F 
0  54 
C+ 
75  79 


Attendance Policy: Attendance at all classes will be recorded and is mandatory. Please make sure you read and fully understand the Math Department’s Attendance Policy. This policy will be strictly enforced.
Homework and Quiz Policy: Homework will be assigned every week in class/on canvas. In addition, quiz would be given in class.
Software: Minitab/Excel will be used in the course for activities/assignments/demonstration in class lectures. Smartphone/laptop will be needed for inclass practice problems and activities.
Exams: There will be two midterm exams held in class during the semester and one comprehensive final exam. Exams are held on the following days:
Midterm Exam I 
March 11, 2019 
Midterm Exam II 
April 15, 2019 
Final Exam Period 
May 10  16, 2019 
The final exam will test your knowledge of all the course material taught in the entire course. Make sure you read and fully understand the Math Department's Examination Policy. This policy will be strictly enforced.
Makeup Exam Policy: There will be No makeup QUIZZES OR EXAMS during the semester. In the event an exam is not taken under rare circumstances where the student has a legitimate reason for missing the exam, the student should contact the Dean of Students office and present written verifiable proof of the reason for missing the exam, e.g., a doctor’s note, police report, court notice, etc. clearly stating the date AND time of the mitigating problem. The student must also notify the Math Department Office/Instructor that the exam will be missed.
Cellular Phones: All cellular phones and other electronic devices must be switched off during all class times.
Additional Resources
Math Tutoring Center: Located in the Central King Building, Lower Level, Rm. G11 (See: Spring 2019 Hours)
Further Assistance: For further questions, students should contact their instructor. All instructors have regular office hours during the week. These office hours are listed on the Math Department's webpage for Instructor Office Hours and Emails.
All students must familiarize themselves with and adhere to the Department of Mathematical Sciences Course Policies, in addition to official universitywide policies. The Department of Mathematical Sciences takes these policies very seriously and enforces them strictly.
Accommodation of Disabilities: Disability Support Services (DSS) offers long term and temporary accommodations for undergraduate, graduate and visiting students at NJIT.
If you are in need of accommodations due to a disability please contact Chantonette Lyles, Associate Director of Disability Support Services at 9735965417 or via email at lyles@njit.edu. The office is located in Fenster Hall Room 260. A Letter of Accommodation Eligibility from the Disability Support Services office authorizing your accommodations will be required.
For further information regarding self identification, the submission of medical documentation and additional support services provided please visit the Disability Support Services (DSS) website at:
Important Dates (See: Spring 2019 Academic Calendar, Registrar)
Date 
Day 
Event 
January 22, 2019 
T 
First Day of Classes 
February 1, 2019 
F 
Last Day to Add/Drop Classes 
March 17  24, 2019 
Su  Su 
Spring Recess  No Classes, NJIT Open 
April 8, 2019 
M 
Last Day to Withdraw 
April 19, 2019 
F 
Good Friday  No Classes, NJIT Closed 
May 7, 2019 
T 
Friday Classes Meet/ Last Day of Classes 
May 8 & 9, 2019 
W & R 
Reading Days 
May 10  16, 2019 
F  R 
Final Exam Period 
Course Outline
Please note: Assignments will be assigned in class/canvas.
 ST: Statistics using Technology by Kathyrn Kozak
 IS : Introductory Statistics v1.0 by Douglas S. Shafer and Zhiyi Zhang
Week # 
Textbook and
Chapter # 
Topic 
Week 1
1/24 [R] 
ST chapter 1 
Introduction: Statistics and Sampling 
ST chapter 1 
Introduction: Statistics and Sampling 
Week 2
1/31 [R] 
ST chapter 2 
Descriptive Statistics: Frequency Distribution, Histogram, Bar Graph, Pie chart, Pareto chart, Dot plot, and related topics 
IS Chapter 2 

IS chapter 2 
Descriptive Statistics: Stem and Leaf Display 
Week 3
2/7 [R] 
IS chapter 2 
Descriptive Statistics: Measures of central tendency, Measures of variability, Measures of relative position 
IS chapter 2 
Descriptive Statistics: Boxand Whisker Plot 
Week 4
2/14 [R] 
IS chapter 10 
Correlation and Regression: Scatter Diagram and Linear Correlation 
IS chapter 10 
Correlation and Regression: Linear Regression 
Week 5
2/21 [R] 
IS chapter 3 
Basic concepts of probability 
IS chapter 3 
Basic concepts of probability 
Week 6
2/28 [R] 
IS chapter 4 
Discrete random variable: Introduction to Random Variables and Probability Distributions 
IS chapter 4 
Discrete random variable: Binomial Probabilities 
Week 7
3/7 [R] 
IS chapter 4 
Discrete random variable: Additional Properties of the Binomial Distribution 

REVIEW FOR EXAM #1 
Week 8
3/14 [R] 

MIDTERM EXAM I: Monday ~ March 11, 2019 
IS chapter 5 
Continuous random variable: Normal Probability Distribution 
3/17[S] to 3/24[S] 
SPRING RECESS (NO CLASSES) 
Week 9
3/28 [R] 
IS chapter 5 
Continuous random variable: Areas under Standard Normal Distribution, Areas under any Normal Curve 
IS chapter 6 
Sampling Distributions: Introduction 
Week 10
4/4 [R] 
IS chapter 6 
Sampling Distributions: Sampling Distribution continued, The Central Limit Theorem 

(WITHDRAWAL DEADLINE Monday, April 8, 2019) 
Week 11
4/11 [R] 
IS chapter 7 
Estimation: Large sample and small sample estimation of the population mean 

REVIEW FOR EXAM #2 
Week 12
4/18 [R] 

MIDTERM EXAM II: Monday ~ April 15, 2019 
IS chapter 7 
Estimation: Estimation of population proportion; sample size considerations 
Week 13
4/25 [R] 
IS chapter 8 
Testing Hypotheses: Elements of hypothesis testing, Large sample tests for a population mean 
IS chapter 8 
Testing Hypotheses: Small sample tests for a population mean 
Week 14
5/2 [R] 
IS chapter 8 
Testing Hypotheses: Large sample tests for a population proportion 

REVIEW FOR FINAL EXAM 


Reading Day 5/8 and 5/9 (W & R) 
5/10  5/16 

Final EXAM WEEK 
Updated by Professor P. Natarajan  1/21/2019
Department of Mathematical Sciences Course Syllabus, Spring 2019