STATISTICS

BASIC

TYPES OF DATA

DR. FARHANA SHAHEEN

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 POPULATION

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

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 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.

PRIMARY DATA

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

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.________________________