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.                 

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 Primary data ObservationExperimentationSurvey Secondary data Print or Electronic

Types of data Numerical data Continuous: -Weight -Height Numerical data Discrete data: -Number of children -Number of eggs produced per day Categorical data: -Marital status -Sex -Eye color DataNumericalDiscreteContinuousCategorical

Discrete data or continuous data? 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: ExampleType of dataLevel of measurement Profit($) Religion Gender Managerial level Height Rank in army