Course

# Introduction to Statistics

Faculty
Science & Technology
Department
Mathematics
Course Code
MATH 1160
Credits
3.00
Semester Length
15 weeks
Max Class Size
35
Method(s) Of Instruction
Lecture
Tutorial
Typically Offered
Fall
Summer
Winter

## Overview

Course Description
A pre-calculus introduction to descriptive statistics, measures of central tendency and variation, elementary probability, probability distributions, sampling, hypothesis testing, regression, and correlation.
Course Content

Introduction to Statistics

• The nature of data, uses and abuses of statistics, design of experiments statistics with calculator and computers.

Describing exploring and comparing data

• Summarizing data with frequency tables, pictures of data, measures of central tendency, measures of variation, measures of position, exploratory data analysis.

Probability

• Definitions, addition rule, multiplication rule, probabilities through simulation, counting.

Probability Distributions

• Random variables
• Binomial experiments, mean, variance and standard deviation for the Binomial distribution.
• Other probability distribtuions such as the uniform, geometric, and Poisson (optional).
• Mean and variance of linear combinations of independent random variables.

Normal Probability Distributions

• The Standard Normal distribution, non-standard Normal distributions, the Central Limit Theorem, Normal approximation to the Binomial distribution.

Estimates and Sample Sizes

• Estimating a population mean using samples, estimating a population proportion.
• Determining a sample size.

Hypothesis Testing

• Fundamentals of Hypothesis Testing, testing a claim about a mean using large and small samples, testing a claim about a proportion.
• Confidence intervals.

Inferences from Two Samples

• Inferences about two means: dependent samples, inferences about two means: independent and large samples, inferences about two means: independent and small samples, inferences about two proportions

Correlation and Regression

• Computing and interpreting the meaning of the correlation coefficient and coefficient of determination.
• Constructing and applying linear models to make predictions.
Learning Activities

Lectures, group work, assignments.

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 some of the following:

 Weekly quizzes 0-20% Term tests 20-70% Tutorials 0-10% Participation/attendance 0-5% Assignments 0-10% Final exam 30-40%

Note:  Students may be required to pass the final exam in order to be eligible to pass the course.

Learning Outcomes

At the end of the course, the successful student will be able to:

• Define the terms “population” and “sample” as they apply to Statistics
• Define and differentiate between the nominal, ordinal, interval and ratio levels of measurement
• Explain the proper use of Statistics within real world application and provide examples of its abuse
• Have an understanding of experimental design and the use of random number tables and generators
• Create and interpret frequency tables, histograms, cumulative frequency tables, stem and leaf displays and scatter plots
• Calculate and interpret measures of central tendency and variation
• Calculate and interpret standard scores
• Use the classical and relative frequency approaches to probability and counting techniques to solve problems
• Know and apply the addition and multiplication rules for probability and the concept of conditional probability
• Be able to differentiate between discrete and continuous random variables
• Determine whether the conditions for a Binomial experiment apply and compute the Binomial probabilities
• Compute the mean, variance and standard deviation for the Binomial distribution
• Compute the mean and variance of a linear combination of independent random variables (optional)
• Determine probabilities of standard and non-standard normal random variables
• Use the Normal distribution to approximate Binomial probabilities
• Apply the Student t distribution
• Apply the Central Limit Theorem to estimate probabilities associated with sample spaces when the population is sufficiently large
• Perform hypothesis tests on population parameters or the difference between population parameters.
• Create confidence intervals for population parameters or their difference using large and small samples.
• Create Contingency Tables and perform goodness-of-fit testing in multinomial experiments using the Chi-square test. (optional)
• Apply Chebychev’s theorem (optional)
• Apply the Poisson and other probability distributions (optional)
Textbook Materials

Consult the Douglas College bookstore for the current textbook. Sample textbooks:

Triola, Essentials of Statistics, Pearson, current edition
De Veaux et al, Stats: Data and Models, Pearson, current edition
Moore, Basic Practice of Statistics, Freeman, current edition

A calculator with statistical functionality may also be required.

## Requisites

### Prerequisites

MATH 1105; or

Precalculus 11 with a B or better; or

Precalculus 12 with a C or better; or

Foundations of Math 11 with a B or better; or

Foundations of Math 12 with a C or better.

### Corequisites

No corequisite courses.

### Equivalencies

No equivalent courses.

## Course Guidelines

Course Guidelines for previous years are viewable by selecting the version desired. If you took this course and do not see a listing for the starting semester / year of the course, consider the previous version as the applicable version.

## Course Transfers

These are for current course guidelines only. For a full list of archived courses please see https://www.bctransferguide.ca

Institution Transfer Details for MATH 1160
Athabasca University (AU) AU MATH 215 (3)
BC Institute of Technology (BCIT) BCIT MATH 2403 (3.5) or BCIT MATH 2453 (5)
Camosun College (CAMO) CAMO STAT 116 (3)
Capilano University (CAPU) CAPU STAT 101 (3)
Coast Mountain College (CMTN) CMTN MATH 131 (3)
College of New Caledonia (CNC) CNC MATH 104 (3)
College of the Rockies (COTR) COTR STAT 106 (3)
Coquitlam College (COQU) COQU STAT 101 (3)
Kwantlen Polytechnic University (KPU) KPU MATH 1115 (3)
Langara College (LANG) LANG STAT 1123 (3) or LANG STAT 1124 (3)
North Island College (NIC) NIC STA 115 (3)
Okanagan College (OC) OC STAT 121 (3)
Simon Fraser University (SFU) SFU STAT 201 (3) or SFU STAT 203 (3) or SFU STAT 205 (3)
Thompson Rivers University (TRU) TRU STAT 2000 (3)
Trinity Western University (TWU) TWU MATH 102 (3)
University of British Columbia - Okanagan (UBCO) UBCO STAT 121 (3)
University of British Columbia - Vancouver (UBCV) UBCV STAT 203 (3)
University of Northern BC (UNBC) UNBC STAT 240 (3)
University of the Fraser Valley (UFV) UFV STAT 104 (4)
University of Victoria (UVIC) UVIC STAT 255 (1.5)
Vancouver Community College (VCC) DOUG MATH 1160 (3) or DOUG PSYC 2300 (3) = VCC MATH 1111 (3)
Vancouver Island University (VIU) VIU MATH 161 (3)

## Course Offerings

### Summer 2023

CRN
Days
Dates
Start Date
End Date
Instructor
Status
CRN
22258
Tue Thu
Start Date
-
End Date
Start Date
End Date
Instructor Last Name
Marquise
Instructor First Name
Annie
Course Status
Open
Section Notes

MATH 1160 001 - Students must ALSO enroll in MATH 1160 T01 or T02.

Max
Enrolled
Remaining
Waitlist
Max Seats Count
35
Actual Seats Count
20
15
Actual Wait Count
0
Days
Building
Room
Time
Tue Thu
Building
Coquitlam - Bldg. A
Room
A1230
Start Time
12:30
-
End Time
14:20
CRN
Days
Dates
Start Date
End Date
Instructor
Status
CRN
22259
Tue Thu
Start Date
-
End Date
Start Date
End Date
Instructor Last Name
Meichsner
Instructor First Name
Alan
Course Status
Waitlist
Section Notes

MATH 1160 002 - Students must ALSO register in MATH 1160 T03, T04 or T05.

Max
Enrolled
Remaining
Waitlist
Max Seats Count
35
Actual Seats Count
35
0
Actual Wait Count
7
Days
Building
Room
Time
Tue Thu
Building
New Westminster - North Bldg.
Room
N1220
Start Time
12:30
-
End Time
14:20
CRN
Days
Dates
Start Date
End Date
Instructor
Status
CRN
22813
Wed Fri
Start Date
-
End Date
Start Date
End Date
Instructor Last Name
Meichsner
Instructor First Name
Alan
Course Status
Waitlist
Section Notes

MATH 1160 003 - Students must ALSO register in MATH 1160 T03, T04 or T05.

Max
Enrolled
Remaining
Waitlist
Max Seats Count
35
Actual Seats Count
35
0
Actual Wait Count
5
Days
Building
Room
Time
Wed Fri
Building
New Westminster - North Bldg.
Room
N1220
Start Time
10:30
-
End Time
12:20