Basics stat ppt-types of data

BASIC
STATISTICS
TYPES OF DATA
DR. FARHANA SHAHEEN

SYLLABUS
FOR Wk-1
Statistics
Definition
Population and Sample
Data Types
- Quantitative Data
- Qualitative Data
Stem and Leaf diagram
Line Charts and Scatter Diagrams

Week-II
Describing Data and Measurement
- Measure of Center and Location
a. Population Mean
b. Sample Mean
c. Median
Examples
d. Mode
Examples
Bar Charts
Pie Charts

What is Statistics?
Statistics :
Definition. A collection of tools and techniques that are used
to convert data into meaningful information.
Statistics is the study of collecting, organizing and
summarizing data, used to convert data into a meaningful
information.

What does a statistician do?
• Collects numbers or data
• Systematically organizes or arranges the data
• Analyzes the data…extracts relevant information to
provide a complete numerical description
• Infers general conclusions about the problem using this
numerical description

Population:
Population: is the universal set of all objects under
study.
A population is any entire collection of people, animals,
plants or things from which we may collect data. It is
the entire group we are interested in, which we wish to
describe or draw conclusions about.
For example:
Students of YUC
People living in Saudia
Bulbs made in a factory
Different models of cell phones

Population
A population is a collection of data whose
properties are analyzed. The population is
the complete collection to be studied, it
contains all subjects of interest

Sample: (Subset of the Population)
A sample is a group of units selected from a larger
group (the population). By studying the sample it is
hoped to draw valid conclusions about the larger group.

Populations and Samples
Population
The term "population" is used in statistics to represent all possible
measurements or outcomes that are of interest to us in a particular
study."
Sample
A subset of the population is known as a Sample.

SAMPLE SIZE
Sample size is the number of
observations used for calculating
estimates of a given population.
For example, if we interviewed 30
random students at a given high
school to see if they liked a certain
movie star, "30 students" would be our
sample size.
All students in the school is
Population.

Examples:
1. You want to know the average height of men
aged 15-30
Population: Everyone in that age range
Sample: selections made from the population
2. The population for a study of infant health for
all Children born in 1980.
The sample might be all babies born on 7th May
in any of the years
There are also various ways in selecting the
sample.

3. Population: All Saudis who played
soccer during the last year.
Sample: Random number and
samples of those people selected.

Data : A collection of facts or information.
Examples:
Restaurants in Saudi
Arabia.
Types of Cars
Heights of all students in
your class
Age of all students in
YUC

Example:
Find the heights of all students in your
class. Organize and summarize the
data.

Statistic in real life?
How many of you like Albaik,
KFC, McDonalds, or Pizza
hut?
Albaik 32%
KFC 36%
McDonalds 11%
All 21%

DIFFERENT TYPES OF
DATA:
1. Primary Data
2. Secondary Data
3. Qualitative Data
4. Quantitative Data

Primary and Secondary Data
Data can be classified as either Primary
or Secondary.
Primary Data:
Primary data means original data that
has been collected specially for the
purpose in mind. It means when an
authorized organization, investigator or
an enumerator collects the data for the
first time from the original source. Data
collected this way is called primary data.
For example: Your own questionnaire,
survey, information.

Survey : Are Pepsi/Coke bad for
health?
1) Strongly Agree
2) Agree
3) Neutral

Secondary Data:
Secondary data is data that has been
collected for another purpose. When we
use Statistical Method with Primary Data
from another purpose for our purpose we
refer to it as Secondary Data. It means
that one purpose's Primary Data is
another purpose's Secondary Data.
Secondary data is data that is being
reused. Usually in a different context.
For example: Data from a Book,
Newspaper, Magazine, or Internet.

Other Types of Data
Qualitative Quantitative
Discrete Continuous

Qualitative Data
• Qualitative Data measures a quality or characteristic on each
experimental unit. It is a categorical data.
• Examples:
•Hair color (black, brown, blonde, white, grey, mahogany)
•Make of car (Dodge, Honda, Ford, Toyota)
•Gender (male, female)
•Place of birth (Riyadh, Jeddah, Yanbu)

Quantitative Data
Quantitative data is a numerical measurement
expressed in terms of numbers.
For example: Temperature= “26 degrees"
Height = "1.8 meters"
Length = “2.5 feet”
Age = “9 years”
Note: Quantitative data always are associated with
a scale measure (degree/feet/years).

•Quantitative Data measure a numerical
quantity on each experimental unit.
Examples
• For each orange tree, the number of oranges
is measured.
– Quantitative
• For a particular day, the number of cars
entering a college campus is measured.
– Quantitative
• Time until a light bulb burns out (4 months)
– Quantitative

Qualitative vs Quantitative
Data
Qualitative Data Overview:
Deals with descriptions.
Data can be observed but not
measured.
Colors, textures, smells, tastes,
appearance, beauty, etc.
Qualitative → Quality

Quantitative Data Overview
Quantitative Data: Deals with
numbers.
Data which can be measured.
Length, height, area, volume, weight,
speed, time, temperature, humidity,
sound levels, cost, members, ages,
etc.
Quantitative → Quantity

Example 1: Oil Painting
Qualitative data:
blue/green color, gold frame
smells old and musty
texture shows brush strokes of oil paint
peaceful scene of the country
masterful brush strokes
Quantitative data:
picture is 10" by 14"
with frame 14" by 18"
weighs 8.5 pounds
surface area of painting is 140 sq. in.
cost $300

Example 2: Coffee Latte
Qualitative data:
robust aroma
frothy appearance
strong taste
burgundy cup
Quantitative data:
12 ounces of latte
serving temperature 150º F.
serving cup 7 inches in height
cost $4.95

Example 3: MAL-001 Class
Qualitative data:
Students
Girls
Smart/Intelligent
Hard working
Quantitative data:
32 students
6 A grades
68% on honor roll (3.75 gpa or more)
15 students good in mathematics

Discrete and Continuous Data
There are two types of Quantitative Data:
1. Discrete (in whole numbers)
Exp: Number of Questions in Exam 5, 7, 14
Number of cars,
Number of students 3000
2. Continuous (in decimal points)
Exp: Temperature of Yanbu on Sunday 26.5
degrees
Your Height 5.3”
Your Weight 120.5 lbs
Shoe size 7.5

Discrete and Continuous Data
Discrete data usually occurs in a case
where there are only a certain number of
values, or when we are counting
something (using whole numbers).
Continuous data makes up the rest of
numerical data. This is a type of data
that is usually associated with some sort
of physical measurement (like
feet/inches/kilogram).

Question:
Check for Discrete or
Continuous:
Your phone number
Height of a tree
Id number
Length of a skirt
The number of goals scored by a
hockey team
The number of subjects your school
offered
Shoe size

Exercise:1
Classify each set of data as discrete or
continuous.
1) The number of suitcases lost by an airline.
2) The height of corn plants.
3) The distance of your house to YUC.
4) The number of green M&M's in a bag.
5) The time it takes for a car battery to die.
6) The production of tomatoes by weight.

Exercise-2
Identify each of the following variables as qualitative
or quantitative, if quantitative is it discrete or
continuous?
•Weight of two dozen shrimps.
________________________
•A person’s body temperature.
_________________________
•Rating of a newly-hired lecturer in the University
(excellent, good, fair, poor)._____________________
•Number of people waiting for treatment at a hospital
emergency room.________________________

Basics stat ppt-types of data

Basics stat ppt-types of data

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Basics stat ppt-types of data