Transcript IIC University of Technology Course: Statistics and

IIC University of Technology
Course: Statistics and Probability
Year 2 & 4, semester 1
Lecturer: Mr. Yuk Sovandara
Chapter 1
Introduction to Statistics and Data
Collection
What is Statistics?
•A branch of mathematics taking and
transforming numbers in to useful information
for decision makers
•Methods for processing and analyzing numbers
•Methods for helping reduce the uncertainty in
decision making
What can statistics apply to?
• Business research
• Technical reports
• News articles
• Magazine articles
Why study Statistics?
• Present and describe data and information
properly
• Draw conclusion about large groups of
individuals, or items by using information
from samples.
• Make reliable forecasts about a business
activity
• Improve business processes
In pairs think why you need to know statistics?
To know how to properly………….information
To know how to draw conclusions about
populations based on sample………..
To know how to………processes
To know how to obtain reliable…………..
Type of statistics
1. Descriptive statistics—methods of
collecting, summarizing, and describing data
Example:
Ministry of Economy and Finance reports
that in 2011, the economic growth rate is up
to 6.7%
2. Inferential statistics—methods of drawing
conclusions or making decision concerning a
population based on sample data
Example:
Based on a sample (30 students’ scores)
selected from 50 students’ scores of an IT
class, more than 15 students got scores higher
than 50. Therefore, we can infer that 50% of
all students in the IT class pass.
• Population: A collection of all possible
individuals or items of interest
• Sample: A portion, or part of the population
In the above example, the sample is 30
students’ scores. The population is all scores
of students in the IT class.
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Example:
Beeline company asked a sample of 30,000
Beeline Sim users where they like numbers
start with 090. Of 30,000, 2,3000 people said
that they like. The company will increase
numbers starting with 090 in the market.
Question:
Is this example of descriptive statistic or
inferential statistics? Why?
Why collect data?
• A marketing research analyst needs to assess
the effectiveness of a new advertisement
• An operating manager wants to monitor a
manufacturing process to find out whether
the quality of the product being manufactured
is conforming to company standards.
• RGC wants to find out whether triangle
strategy has reduced the poverty of
Cambodian.
Collecting data
Secondary
data
Primary data
Observation
Experimentation
Survey
Print or
Electronic
Types of data
Categorical data:
-Marital status
Data
-Sex
-Eye color
Numerical data
Discrete data:
-Number of children
Numerical
Categorical
-Number of eggs produced per
day
Numerical data
Continuous:
-Weight
-Height
Discrete
Continuous
Discrete data or continuous data?
•
•
•
•
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The units of an item in an inventory
The number of persons per household
The weight of a car
The length of time that a car racer uses
The average number of persons in a large
community
Levels of measurement
An ordinal level classifies data in to distinct
categories in which ranking is implied.
Example:
-Student grades: A, B, C, D
-Satisfaction: Satisfied, neutral, unsatisfied
-Standard & Poor’ bond rating: AAA, AA,A,
BBB,BB, B, CCC, CC, C,DDD, DD,D
A nominal level classifies data in to distinct
categories in which no ranking is implied.
Example:
-Internet providers: Angkornet, Online, Camnet
-Sex: M, F
An interval level is a level in which the
difference between measurements is a
meaning full quantity but the measurements
do not have a true zero point.
Example: Temperature in Fahrenheit
An ratio level is a level in which the difference
between measurements is a meaning full
quantity but the measurements have a true
zero point.
Example: Height, Age
Identify the types of data and levels of
measurement in the following examples:
Example
Profit($)
Religion
Gender
Managerial level
Height
Rank in army
Type of data
Level of measurement