# Document 25403445

```MGT201 Mathematical Models
Salkind, Statistics for People Who (Think They) Hate Statistics 6th Edition, SAGE Inc. &copy; 2017
What is Statistics?...and Why Statistics?
Why You Need To Study Statistics:
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What is Statistics?
So, what is statistics?
What is Statistics?
• Statistics is a way of reasoning, along with a
collection of tools and methods, designed to help
us understand the world.
• A set of tools and techniques used for describing,
organizing, and interpreting information or data.
• Statisticians use tools and methods in statistics to:
 Analyze small and large amounts of data
 Analyze data real time
 Interpret the results and help organizations in their
decision making
How is Statistics used in Management?
How is statistical analysis used in
management?
How is Statistics used in Management?
Statistical analysis is used in almost every area in
• Accounting – to audit a company’s accounts
(“statistical audit” is conducted in which a
representative sample of invoices is audited)
• Finance – to decide on which investment
alternatives to invest in (statistics can provide
many ways of measuring risk and expected
returns on investments)
How is Statistics used in Management?
• Marketing– to understand consumer purchasing
patterns, marketers use statistical analysis to learn
about the relationship between various variables
including age group, income level, gender, postal
code, etc. to design promotional campaigns focused
on the appropriate target audience.
• Human Resources Planning – to investigate the
patterns of promotion, recruitment, retirement,
transfers and resignation, an organization analyzes
employee past data to forecast the number of
employees at different levels of the management
pyramid in the future.
How Can I Learn Statistics?
You need to be very proactive in doing the
learning by putting into practice the concepts
and methods the book teaches. Statistics is like
most useful things in life: You must practise it to
really learn it.
Branches of Statistics
What are the two major branches of statistics?
Branches of Statistics
Two major branches of statistics:
a) descriptive statistics
b) inferential statistics
Descriptive Statistics
 Used to organize and describe the
characteristics of a particular data set
 This collection of data is sometimes called a
data set or just data.
Descriptive Statistics Examples
 Average age of everyone in this class (i.e.,
mean)
 The most popular college major (i.e., mode)
Practice (find the mean and mode)
Inferential Statistics
 Used to make inferences based on a smaller
group of data
 A sample is a subset of a population.
 A population is all of the occurrences with a
certain characteristic.
Inferential Statistics Examples
 Take 100 people with depression, and split
them up into two groups randomly.
 With the first group, give them a sugar pill,
and give the second group a new depression
drug.
 If you find a statistically significant difference
in both groups, you infer that you would find
similar results in the entire population as well.
Inferential Statistics Example
Based on an analysis of students in MGT 201,
would you infer that most business students at
Stanford College take the bus to school every
day?
- Raise your hand if you do
Inferential Statistics
Why does statistics use samples to make
presents itself in a population?
Inferential Statistics
It is often necessary to take a sample instead
of studying every member of a population due
to one or more of the following reasons:
1. The prohibitive cost of surveying the whole
population.
2. The destructive nature of some tests.
3. The physical impossibility of capturing the
population.
Cases and Variables
What are cases?
What are variables?
Cases
A row of a data table corresponds to an individual
people) we record some characteristics.
Purchase
Order Number
Cases
Name
Ship to
Province
Price
Area
Code
ASIN
10675489
Katherine
H.
Alberta
10.99
403
N
B0000015Y6
10783489
Samuel P.
Nova
Scotia
16.99
902
Y
B000002BK9
12837593
Chris G.
Quebec
15.98
819
N
B000068ZVQ
15783947
Monique D.
Ontario
11.99
905
N
B000001OAA
Variables
The characteristics recorded about each individual or case
are called variables. These are usually shown as the columns of
a data table and identify What has been measured.
Variables
Purchase
Order
Number
Name
Ship to
Province
Price
Area
Code
ASIN
10675489
Katherine
H.
Alberta
10.99
403
N
B0000015Y6
10783489
Samuel P.
Nova
Scotia
16.99
902
Y
B000002BK9
12837593
Chris G.
Quebec
15.98
819
N
B000068ZVQ
15783947
Monique D.
Ontario
11.99
905
N
B000001OAA
Variable Types
What are the types of variables?
Variable Types
When a variable names categories and
those categories, it is called a categorical
variable (also called qualitative variable).
When a variable has measured numerical
values with units and the variable tells us about
the quantity of what is measured, it is called a
quantitative variable.
Variable Types
Categorical variables …
• arise from descriptive responses to questions like
“What kind of advertising do you use?” or “Do
you invest in stock market?”
• may only have two possible values (like “Yes” or
“No”)
• may be a number like a telephone area code
Variable Types (Categorical)
Question
Categories or Responses
Do you invest in the stock market?
__Yes__No
What kind of advertising do you use?
__Magazines__Internet__Direct Mailings
I would recommend this course to
another student.
__Strongly Disagree__Slightly Disagree__Slightly
Agree__Strongly Agree
How satisfied are you with this
product?
__Very Unsatisfied__Unsatisfied__Satisfied__Very
Satisfied
Variable Types (Quantitative)
Some quantitative variables have units. The units
indicate …
• how each value has been measured
• the corresponding scale of measurement
• how much of something we have
• how far apart two values are
Other quantitative variables have no units, such as …
• Number of visits to a web site
• Number of shares of a company traded in Toronto Stock
Exchange
Variable Types
• Some variables can be both categorical and
quantitative
• How data are classified depends on Why we are
collecting the data
For example, variable Age is obviously the quantitative
value, measured in years, that may be used for finding
the average age of customers.
Age categories such as Child, Teen, Adult, or Senior can
be the categorical value used to decide in which music
to offer in a special deal – folk, jazz, hip hop or reggae.
May take on any value
within a given range of
real numbers and
usually arises from a
measurement (not a
counting) process. Eg.
Height, weight, time,
etc.
May have a finite
number. Mostly comes
from a counting
process. Their values
are mostly whole
numbers (counts). Eg.
Numbers of students,
number of university
credits, etc.
Indicates the rank
ordering of items.
Eg. Customer
product review.
Where, 1: very
satisfied, 2:
Satisfied, 3:
Neutral, 4=
Unsatisfied, 5=
Very unsatisfied.
Words that
describe the
categories or
classes of
response. Eg.
1=Male
2=Female.
Numerical variables
Nominal vs. ordinal categorical
variables
A nominal variable is one that has two or more categories, but there is no
intrinsic ordering to the categories. For example, gender is a categorical
variable having two categories (male and female) and there is no intrinsic
ordering to the categories. Hair color is also a categorical variable having
a number of categories (blonde, brown, brunette, red, etc.) and again,
there is no agreed way to order these from highest to lowest. A purely
categorical variable is one that simply allows you to assign categories but
you cannot clearly order the variables. If the variable has a clear
ordering, then that variable would be an ordinal variable.
 An ordinal variable is similar to a categorical variable. The difference
between the two is that there is a clear ordering of the variables. For
example, suppose you have a variable, economic status, with three
categories (low, medium and high). In addition to being able to classify
people into these three categories, you can order the categories as low,
medium and high. Now consider a variable like educational experience