Course Outline
Course Information
Course Code and Title:
CBST-1090: Introductory Statistics
Course Section:
N/A
Department:
Life Sciences
Program:
Chemical and Biosciences Technology
Total Hours:
48 Hours
Credit Hours:
3
Course Description:
Introductory Statistics will teach students to summarize, analyze, display and
interpret data using various common statistical methods. Methods will include
the use of graphs, tables and numerical descriptive measures. Probability and
probability distributions including normal, Poisson, hypergeometric, and binomial
will be covered. As well, we will investigate means to determine the minimum
size for a sample that will be representative of a population, perform regression
analysis using least squares and calculate and interpret confidence intervals for
population averages proportions. We will consider the use of statistics to
evaluate various hypotheses using chi square, z and t tests. Computer labs will
reinforce theoretical course concepts by having students work through various
statistical evaluations and will teach the use of Microsoft Excel’s statistical
processing functionality.
Recognition of Prior Learning (RPL):
RPL (also known as PLAR – Prior Learning Assessment and Recognition) is a
process in which individuals have the opportunity to obtain credit for college level
knowledge and skills gained outside the classroom and/or through other
educational programs. It is a process which documents and compares an
individual’s prior learning gained from prior education, work and life experiences
and personal study to the learning outcomes in College courses/programs. For
more information about RPL at Red River College, refer to the RPL website at
http://www.rrc.mb.ca/index.php?pid=404.
Contact your course instructor for information regarding RPL processes and
opportunities for this course.
For general information and assistance with RPL, contact Red River College’s
RPL Advisor at 204.632.3094.
Academic Requisites:
Successful completion of CBST-1110 Mathematics
Course Equivalencies:
None
Course Delivery Methods:
Classroom lectures and computer lab sessions.
The following communication tools will be used in this course:
Email
Scheduled and unscheduled consultations with the instructor.
College LEARN site
Course Format:
The course format consists of 24 hours of classroom lectures along with
24 hours of computer lab sessions.
Effective Date:
Sept. 23, 2011
Instructor Information
Instructor’s name: Michael Judge
Email: mjudge@rrc.mb.ca
http://connect.rrc.ca/Instructors/mjudge/default.aspx
Office phone: 632-2566
Office location: A425B
Office hours: Typically 8:00 – 4:00 although students are strongly encouraged to
make an appointment if they require consultation with the instructor.
Student Readiness
Technology & Equipment Readiness:
A scientific calculator such as the inexpensive Texas Instruments TI-30Xa is
recommended. Note that a calculator without programmable functions is
required for examinations.
A portable USB memory stick is recommended to save data from computer labs.
Student Commitments and Contact Times:
Students are expected to attend all lectures.
Course Resources:
Text books:
“Practical Statistics by Example Using Microsoft Excel and Minitab”, 2nd
edition,
Terry Sincich, David M. Levine, David Stephan
Prentice Hall,
ISBN 0-13-041521-9
Resources:
During the course, various material will be available on the course LEARN
site. This material may include handouts, additional reference material and
useful online resource links.
Student Learning
Learning Outcomes:
By the end of this course of study, you should be able to....
understand and utilize various numerical descriptive measures such as
mean and standard deviation. You will also be able to use Microsoft Excel
to carry out and display basic statistical analyses. Additionally, you will
have the ability to; determine the appropriate distribution and calculate
probabilities for an event, find the minimum size for a sample that will be
representative of a population, calculate and interpret confidence intervals
for a population based on sample data, evaluate various statistical
hypotheses using z and t tests, and perform regression analyses.
Instructional Schedule:
Unit
Topic
1
Introduction: Statistics and Data
2
Exploring Data with Graphs and Tables
3
Exploring Quantitative Data with Numerical Descriptive
Measures
4
Probability: Basic Concepts
5
Discrete Probability Distributions
6
Normal Probability Distributions
7
Estimation of Population Parameters using Confidence
Intervals: One Sample
8
Testing Hypotheses re Population Parameters: One
Sample
9
Inferences about Population Parameters: Two Sample
10
Regression Analysis
Important Dates:
NOTE: The following dates are subject to change based on the needs of students, or
scheduling constraints, at the instructor’s prerogative. Students will be notified ahead of
time of any changes.
Date
Event/Deadline
January 3rd
First day of classes
Week of Jan 30th
Mid term exam
February 6th
Voluntary withdrawal deadline
Week of Feb 27th
Final exam
Assessment and Evaluation:
The final course mark will be calculated as follows.
Assessment
Weight
Computer lab assignments
40%
Mid term exam
20%
Final exam
40%
Total:
100%
The 40% allotted to computer lab assignments will be evenly divided between the labs
assigned. Up to seven labs will be assigned depending on time and scheduling
constraints. The specific lab assignments are listed below.
Lab
Topic
1
Introduction to Statistics and Excel
2
Graphing
3
Histograms
4
Basic Probability
5
Probability Distributions
6
Confidence Intervals
7
Hypothesis Testing
Letter Grade Distribution
A+
4.5
90 to 100%
A
4.0
80 to 89%
B+
3.5
75 to 79%
B
3.0
70 to 74%
C+
2.5
65 to 69%
C
2.0
60 to 64%
D
1.0
50 to 59%
F
0.0
0 – 49%
Course Policies
General Academic Policies:
It is the student's responsibility to be familiar with and adhere to the Red River
College (RRC) Academic Policies. These Policies can be found in the RRC
calendar or online under “A SERIES – ACADEMIC MATTERS at
http://www.rrc.mb.ca/index.php?pid=4523.
Supplementary Policies:
Grade requirements: A student must achieve a cumulative grade of 60% (C) of
higher in order to pass this course. A mark of less than 60% will not enable a
student to progress.
Test notes: Both the mid term test and final exam are closed book. However,
students are permitted to bring to these exams one page of notes which they
may reference during the test/exam. The specifications for these notes are as
follows; the notes must amount to no more than both sides of a single standard
8.5 x 11 sheet of paper, they may be either hand-written or typed/printed, they
must have been made by the student (i.e. not a professional study guide or a
textbook photocopy or a printout of a web page), and notes must be used only by
the student that made them and cannot be exchanged by students during the
exam.
Final exams: Except under special circumstances (such as for medical reasons)
if the final exam is missed, the student will receive a mark of zero for that exam.
Marked final exams are not returned to the student after marking; however final
exams may be reviewed with the instructor within one month of writing.
Mid term exams: Except under special circumstances (such as for medical
reasons) if the mid term exam is missed, the student will receive a mark of zero
for that exam. Marked mid term exams are returned to students.
Assignments: Typically, all lab assignments are due at the end of the computer
lab session unless otherwise specified by the instructor. Late assignments will
not be accepted after the assignments have been marked and returned to the
class and will receive a mark of zero. Marked assignments are returned to
students.
Supplemental exams: No supplemental exams are allowed for mid term exams
but rather only for final exams. Students who attain an overall GPA for the term
of 1.5 or higher will be eligible to write a supplemental exam if they do not attain
a passing grade on the course. Marked supplemental exams are not returned to
students.
See the latest edition of the Chemical and Biosciences Technology Student
Handbook for additional policies and information.
Date Revised: September 30, 2011
Acknowledgements:
Not applicable
Additional Information/Frequently Asked Questions:
Not applicable
Authorization:
This course is authorized for use by:
___________________________________ __________________________
Isabel Bright, Chair, Life Sciences
Date
©Red River College 2011