Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STATISTICS 270
Practice For Test #2 (Chapters 4 6)
*Study the following topic areas. The question types below are representative of the style of questions you will see
on the quiz. The formula sheet at the end of this handout is the same one you will rece
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
3.1 Measures of Central Location
3.2 Measures of Variability
Measures of Central Location
Used to describe data
Determines information about the centre, or middle, of a group of
numbers
Mean
Average of a group of numbers
Add all numbers and d
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
2.2 Frequency Distributions
Frequency Distributions
Visual summary of data in a table
Data is placed into classes/intervals
Classes/intervals are equal size
To find class/interval size, find range and divide by # of classes
Range Highest valu
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
Chapter 5  Probability
Part 1
Methods of Assigning Probabilities
Three general methods
Classical, Relative, and Subjective
Classical Method
Based on laws and rules
Involves experiments and events
P(E) = Probability of event E
n = # of ways
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
3.3 Measures of Relative Standing
Percentiles
Divide a group of data into 100 parts
Used to compare results to each other
NOT THE SAME AS PERCENT!
A student getting 80% in a course does not mean the student is in the 80th
percentile!
No set
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
Chapter 1 Introduction to Statistics
2.1 Types of Data
What is Statistics?
Statistics is a science dealing with the collection, analysis,
interpretation, and presentation of numerical data
Surveys given, results compiled, used to make decisions
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
Chapter 5 Probability Part 2:
Electric Boogaloo
Probability Matrix
A probability matrix is a table that displays values or probabilities for
events
Easy to compute unions, intersections, and conditional probabilities
One event is rows, other i
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
2.2 2.5  Graphs
Data Graphs
Frequency distribution table is nice, but often want visuals
Reduces important data into a clear, concise graphic
Quantitative and qualitative types
Quantitative Data Graphs
Histograms
Line Graphs
Stem and Leaf
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
6.2 The Binomial Distribution
Discrete Distributions
Many types of probability distributions
Often have situations that follow the same process
Can be named, analyzed, and calculated with specific formulas
The Binomial Distribution
Used when
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
3.4 Measures of Linear
Relationship
Covariance
Measure of relationship between two variables
May be positive or negative
Positive: As X increases, so does Y
Negative: As X increases, Y decreases
Population
Sample
Computational Formulas for
Co
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
Chapter 4 Data Collection and Sampling
Observational Studies vs Experiments
Source of sampling data may be observational or experimental
Observational Studies: Observe, measure, and record data, but dont
interfere or modify
Experiment: Apply s
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STAT 270
6.1 Discrete Distributions
Distributions
A random variable is a variable that can represent all the possible
outcomes of an experiment
Eg. Experiment is flipping a coin 4 times.
X = # of heads
X = 0, 1, 2, 3, or 4
Discrete vs Continuous
Random
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STATISTICS 270
Practice For Test #3 (Chapters 8 9)
*Study the following topic areas. The question types below are representative of the style of questions you will see
on the quiz. You may bring your brain, writing implements, and your calculator to the q
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STATISTICS 270: Practice for Midterm
Note: Use each of these sample questions to study the concepts that will be tested on the upcoming exam.
Be familiar with any terminology, formulas, rounding (ie. significant digits) rules connected with each
concept.
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
Statistics 270 Final Exam Review
Chapters 8 22 as covered
1. The mean family income in Alberta is $28,500 with a standard deviation of $2600. What is the
probability that a sample of 60 families from Alberta will have a mean income between $28,000
and $29
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
STATISTICS 270
Practice For Test #4 (Chapters 10  15)
*Study the following topic areas. The question types below are representative of the style of questions you will see
on the test. The formula sheet at the end of this handout is the same one you will
Southern Alberta Institute of Technology (SAIT) (SAIT Polytechnic)
QUANTATIVE METHODS
SCHOOL OF STAT270

Spring 2016
INDIVIDUAL ASSIGNMENT  NEWS ITEM
Ensuring your supply chain is ready for Natural Disasters by Reg Kenney, President
of Engineering and Manufacturing at DHL
Reference
http:/www.supplychaindigital.com/supplychainmanagement/4474/Ensuringyoursupplychainis