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Revision Date: 10-Apr-14

MAT-2021-VR02 - Statistics I


Synonym: 124802
Location: Rutland
Credits: 3 (45 hours)
Day/Times: Monday & Thursday, 09:00AM - 12:00PM
Semester Dates: 06-23-2014 to 08-07-2014
Faculty: Patricia Gordon | View Faculty Credentials
Faculty Email: ppg01080@csc.vsc.edu
Materials/Lab Fees: $0

Course Description:

An introduction to the basic ideas and techniques of probability and statistics. Topics may include numerical and graphical descriptive measures, probability, random variables, the normal distribution, sampling theory, estimation, hypothesis testing, correlation and regression. The use of technology may be required. Students must take a math assessment for placement purposes prior to registration.

Essential Objectives:

1. Outline the general development of statistical science, and list a number of common applications of statistical methodology.
2. Distinguish between descriptive and inferential statistics.
3. Create and apply various techniques used to describe data, such as pie charts, bar graphs, frequency tables, and histograms.
4. Define three common measures of central tendency (mean, median, and mode), and demonstrate the ability to calculate each manually from a series of small data sets.
5. Describe common methods of measuring variability, including range, percentiles, variance, and standard deviation, and calculate each from a series of small data sets.
6 Explain the Normal Probability Distribution, techniques of sampling, the Central Limit Theorem, and the concept of standard error, and compute probabilities associated with normally distributed samples.
7. Test hypotheses about the value of the mean assuming the normal distribution and large sample results.
8. Select and perform common statistical tests including one- and two-tailed tests.
9. Define linear regression and correlation and discuss their applications
10. Interpret and evaluate the validity of statistical data and reports.
11. Demonstrate proficiency in understanding, interpreting, evaluating and applying quantitative data and information.

Methods:

 
  • Lecture
  • Small Group Discussions
  • Large Group Discussions
  • Class Work

Evaluation Criteria:

Your grade is based on a point system.
Chapter Problem Sets: 50-100
Tests: 100-150
Attendance: 5 
Final Exam: 100-150
Late assignments receive a 10 % deduction for every class it is late. Assignments are due at the beginning of class. If the assignment is not received at the start of class it will be considered late.

Grading Criteria:


A 90-100  average and at least 13 classes attended
B 80-89  average and at least 12 classes attended
C 70-79 average and at least 11 classes attended
D 60-69 average and at least 11 classes attended
N 0-59 average or fewer than 11 classes attended

Textbooks:

Summer 2014 textbook data will be uploaded on May 2. We strongly suggest that you verify the information below with our online bookseller EdMap before purchasing textbooks from another vendor. If your course is at the Winooski center, check the UVM Bookstore for textbook and pricing information.

Attendance Policy:

Attendance is essential for your success in this class. Missing three (3) classes may result in a non-satisfactory grade. A pattern of arriving late and leaving early causes disruption and may result in a marked absence.
For each class attended you will receive (5) points. If you leave early or arrive late points may be deducted from the attendance grade for that class.

Faculty Contact Information:

Email Address: Patricia.Gordon@ccv.edu

Syllabus:

** Subject to change over the course of the semester.

Class

Class Notes Class Work/Assignment


  • Introduction to Statistics
  • Problem Set 1

 2


  • Organizing data
  • Frequency Distributions, Histograms, and Related Topics
  • Bar Graphs, Circle Graphs, Time-Series Graphs
  • Stem-and-Leaf Displays
  • Problem Set 2

 3


  • Measures of Central Tendency: Mode, Median, and Mean
  • Measures of Variation

 4


  • Percentiles and Box-amd-Whisker Plots
  • Correlation and Regression - Scatter Diagrams, Linear Correlation

 5


  • Linear Regression and the Coefficient of Determination

 6

  • Chapter 1,2,3,4 Review Test 1
  • Test 1

 7


  • Fundamentals of Probability 
  • Addition Rule
  • Multiplication Rule

  8


  • Complements and Conditional Probability
  • Counting Rule, factorials, permutations, combinations

 9


  • Random Variables and Probability Distribution
  • Binomial Probability Distributions
  • Mean, Variance, and Standard Deviation (Binomial Distribution)

 10


  • Review ch 5, 6 Test 2
  • The Standard Normal Distribution Problem Set 6
  • Applications of Normal Distributions

 11


  • Sampling Distributions and Estimators
  • The Central Limit Theorem
  • Normal as Approximation to Binomial

12


  • Estimating a Population Proportion
  • Estimating a Population Mean: standard deviation known
  • Confidence Intervals and Sample Sizes

 13


  • Basics of Hypothesis Testing
  • Testing a claim about a mean: standard deviation known

 14


  • Testing a claim about a proportion

 15


  • Test 3 Review
  • Test 3

 

 

Please note: In order to receive accommodations for disabilities in this course, students must make an appointment to see the Americans with Disabilities Coordinator in their site and bring documentation with them.

Academic Honesty: CCV has a commitment to honesty and excellence in academic work and expects the same from all students. Academic dishonesty, or cheating, can occur whenever you present -as your own work- something that you did not do. You can also be guilty of cheating if you help someone else cheat. Being unaware of what constitutes academic dishonesty (such as knowing what plagiarism is) does not absolve a student of the responsibility to be honest in his/her academic work. Academic dishonesty is taken very seriously and may lead to dismissal from the College.

Course description details subject to change. Please refer to this document frequently.

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