basics stat ppt-types of data
TRANSCRIPT
SYLLABUS
FOR Wk-1Statistics
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
PopulationThe 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 15-30Population: Everyone in that age rangeSample: 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 CarsHeights of all students in
your classAge of all students in
YUC
Statistic in real life?
How many of you like Albaik,
KFC, McDonalds, or Pizza
hut?
Albaik 32%
KFC 36%
McDonalds 11%
All 21%
Primary and Secondary Data
Data can be classified as either Primaryor 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.
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.
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
DataQualitative 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.________________________