Probability and Statistics for Science & Engineering

Curriculum guideline

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Course
MATH 2260
Discontinued
No
Course code
MATH 2260
Descriptive
Probability and Statistics for Science & Engineering
Department
Mathematics
Faculty
Science & Technology
Credits
3.00
Start date
End term
Not Specified
PLAR
No
Semester length
15
Max class size
35
Contact hours
Lecture: 4 hours/week Tutorial: 1 hour/week
Method(s) of instruction
Lecture
Tutorial
Learning activities

Lectures, in-class assignments and tutorials.

Course description
Introduction to descriptive statistics, laws of probability, distributions of continuous and discrete random variables, inferential statistics, correlation and linear regression. This course rigorously develops statistical theory and is intended for those students who will continue on in applied disciplines or wish to pursue more statistics courses.
Course content
  1. Descriptive Statistics.
  2. Laws of Probability.
  3. Distributions of Continuous and Discrete Random Variables.
  4. Sampling Distributions and the Central Limit Theorem.
  5. Estimation and Hypothesis Testing.
  6. Regression and Correlation.
Learning outcomes

Students who complete the course successfully will be able to discuss and solve problems involving the following topics:

  • different data types
  • graphical representation of data
  • numerical measures of a data set’s central and dispersive characteristics
  • a sample space and events
  • basic probability rules
  • independence
  • conditional probability
  • Bayes’ theorem
  • general properties of discrete and continuous random variables and their distributions
  • expected value, mean and variance for a random variable with a given distribution
  • binomial, hypergeometric and Poisson distributions
  • normal, gamma and exponential distributions
  • jointly distributed random variables
  • covariance and correlation
  • distributions for sample means and linear combinations of  independent identically distributed random variables
  • central limit theorem
  • estimation of a population mean, difference of means, variance,  proportion or a difference of proportions based on sample data
  • qualification of a claim regarding a mean, difference of means, variance, proportion or a difference of proportions based on sample data
  • scatter plot of bivariate data
  • linear regression model for bivariate data
  • correlation coefficient of bivariate data
  • the use of a significant amount of, and sophisticated level of, technology (such as R, Minitab, SPSS, etc.)
Means of assessment

Evaluation will be carried out in accordance with Douglas College policy.  The instructor will present a written course outline with specific evaluation criteria at the beginning of the semester.  Evaluation will be based on the following criteria:

Quizzes 0-20%
Assignments 0-20%
Attendance 0-5%
In-class work 0-10%
Projects 0-20%
Tutorial 0-10%
Term tests 20-70%
Final exam 30-40%
Textbook materials

Textbook will vary by semester, see College Bookstore for current textbook, example:

Hayter, Probability and statistics for engineers and scientists, (current edition), Duxbury.

Prerequisites

MATH 1120

Corequisites

MATH 1220 (must be taken before or concurrently with MATH 2260)