Smart statistics 2
Upcoming SlideShare
Loading in...5
×
 

Smart statistics 2

on

  • 617 views

 

Statistics

Views

Total Views
617
Views on SlideShare
617
Embed Views
0

Actions

Likes
0
Downloads
2
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Smart statistics 2 Smart statistics 2 Presentation Transcript

  • SMART STATISTICS PREPARED BY: ALI KHAIRI BIN MAZLAN MUHAMMAD SABIQ BIN MOHD NOOR
  • THE QUESTIONS
    • What is statistics?
    • There are two types of data. Name them?
    • Explain their differences?. Give examples for each of them.
    • Find the meaning of these words:-
    • - Population - Variables
    • - Sample - Observation
    • - Data set
  • What is statistics?
    • A function of the set of random variables corresponding to a set of observation.
    • It’s often used to refer to the corresponding function of the data.
    • The word of ‘statistic’ was introduced by Sir Ronald Fisher in 1922.
  • TYPE OF DATA DATA QUALITATIVE DATA QUANTITATIVE DATA
  • TWO TYPES OF DATA
    • DATA FOUND BY QUALITATIVE DATA
    • Overview:
    • Deals with descriptions.
    • Data can be observed but not measured.
    • Colors, textures, smells, tastes, appearance, beauty, etc.
    • Qualitative -> Quality
  • EXAMPLE FOR QUALITATIVE DATA
    • 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
    • Example 2: Latte
    • +
    • Qualitative data:
    • robust aroma
    • frothy appearance
    • strong taste
    • burgundy cup
    • DATA FOUND BY QUANTITATIVE DATA
    • Overview:
    • 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 FOR QUANTITATIVE DATA
    • Example 1: Oil Painting
    • 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: Latte
    • Quantitative data:
    • 12 ounces of latte
    • serving temperature 150º F.
    • serving cup 7 inches in height
    • cost $4.95
  • DIFFERENCE TYPE OF DATA
    • QUALITATIVE DATA
    • Deals with descriptions.
    • Data can be observed but not measured.
    • Colors, textures, smells, tastes, appearance, beauty,
    • QUANTITATIVE DATA
    • Deals with numbers.
    • Data which can be measured.
    • Length, height, area, volume, weight, speed, time, temperature, humidity, sound levels, cost, members, ages,
  • FIND THE MEANING
    • What Is Sample?
    • A subset of population is usually chosen in such way that it can be taken to represent the population with respect to some characteristic. (example: height, or cost, or gender, or make of car)
    • A list of members of the population of interest is called the sampling frame .
    • If each members of the sample is selected by the equivalent of drawing lots, the sample is a simple random sample or commonly a random sample.
  • What is Data Set?
    • In statistics data sets usually come from actual observations obtained by sampling a statistical population , and each row corresponds to the observations on one element of that population.
    • Data sets may further be generated by algorithms for the purpose of testing certain kinds of software .
    • What Is Variables?
    • The characteristic measured or observed when an experiment is carried out or an observation is made. Variables may be non-numerical or numerical. Since a non-numerical observation can always be coded numerically, a variable is usually taken to be numerical. Statistic is concerned with random variables and with variables whose measurement may involve random errors.
    • What Is Observation?
    • A result of an experiment or trial in which a variable, either numerical or categorical, is measured
    • What is Population?
    • The complete set of all people in a country, or a town, or any region.
    • By extension the term is used for the complete set of objects of interest.
    • For example:
    • - All cars built by a particular company in the year 2001.
    • - All apple sold as grade I by a particular supermarket.
    • These all the real population and they are finite.
    • It can be in the larger number.
    • It is also used for infinite population of all possible result of a sequence of statistic trials.
    • For example:-
    • - Tossing a coin.