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Statistics is the science of data collection and analysis.

A population is a very large group which is under study.

Example: The student body at Tennessee Technological University

A sample is a subset of a population.

Example: This class

A parameter is a numerical measurement describing some charactersitic of apopulation.

Example: GPA of all students at TTU

A statistic is a numerical measurement describing some charactersitic of asample.

Example: GPA of this class

Quantitative data is numerical data.

Example: Height, Weight. # of traffic tickets

Qualitative data is nonumerical or verbal data, such as a description.

Example: Hair color, Gender

Discrete data is count or frequency data.

Example; # of traffic tickets

Continuous data is data taken by measurement.

Example: Height, Weight

What is Random Sampling?

Simple Random sample (SRS): every object in a population of objects has a 1in chance of being selected for the sample.

Example: rolling a 6-sided die 4 times to get a sample of size 4

Stratified sample: Take SRS's on each stratum or subpopulation of a population.

The stratum are chosen so that the members share some characteristic.

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Example: Separating a deck of cards into the four suits and then randomlysampling 2 cards from each suit

Systematic sampling: Best by example, take every person from the

phonebook to survey.

Cluster sampling: Divide the population area into sections (or clusters) and thentake an SRS of the clusters. Next, every member of the chosen clusters isincluded in the sample.

Example: Take an SRS of the counties of the United States and then take acensus of those counties

The basic features of statistics as a quantitative or numerical data run a follows:

1. Aggregate of Facts:

Single or isolated figures are not considered to be statistics because such figures

are unrelated and cannot be compared. A single figure of the boy of 26 years

would not constitute statistics. It is just a numerical statement the fact.

Statistical data are concrete numbers which represent objects

2. Systematically Arranged:

A proper plan should be prepared before collecting the statistical data. Data

collected in a haphazard manner would lead to false conclusions. Therefore,data should be collected in a systematic manner.

3. Statistics are Estimated or Enumerated:

According to the feature of statistics, data can be enumerated or estimated. If

the numerical statements are precise accurate, then they can be enumerated.Contrary to this, if the field of investigation large and beyond comprehension,

then the estimation procedure can be adopted.

4. Statistics are numerically expressed:All statistics are expressed numerical figures i.e. expressed in numbers andrelated to quantitative information only. Qualitative characteristics do not come

under statistics unless they are assigned cert; ranks as a quantitative measure of

assessment.

5. Statistical Data Collected for a Pre Determined Purpose:

Collected should be, for a pre determined purpose. The figures are collected

with some goal objective in mind. Without any objective collected data will be

useless. Thus, the purpose of collecting data must be decided in advance.

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6. Placed in Relation to each other:

Numerical information's must be mud related and comparable. In the absence of

such a quality the statistics would se, purpose. For example, statistics related to

number of children born, exports country, coal production etc. have no

relevance for statistical analysis.

Abstract:This paper describes the characteristics of data about wood and wood-

processing products published in Vietnam. The characteristics include

inconsistency of data published by major data sources, lack of necessary data,

and irregular publication frequency. Reasons are identified for the existence ofthe above characteristics of data for the wood and wood-processing industries,

including recent changes in the functions of state statistical organizations and

unclear concepts of data published. These characteristics create difficulties forresearchers and policy-makers working at the Ministry of Agriculture and Rural

Development for analysing policies and establishing supply targets for the wood

and wood-processing industries in 5-year economic plans. To improve thestatistical system, co-operation between state organisations and the information

network (e.g. computers and internet connection) requires strengthening.

Keywords:Engineered-wood product;Conversion rate;Enterprise

definition;Sub-industry;General statistical office

Document Type: Research article

DOI:http://dx.doi.org/10.1007/s11842-010-9138-7Affiliations:1: Statistical Division, Informatics and Statistics Centre forAgriculture and Rural Development, Vietnam Ministry of Agriculture and Rural

Development, Hanoi, Vietnam, Email:

hieu.phansy@uqconnect.edu.au 2: Statistical Division, Informatics and

Statistics Centre for Agriculture and Rural Development, Vietnam Ministry of

Agriculture and Rural Development, Hanoi, Vietnam, Email:thuy_icard@yahoo.com 3: Statistical Division, Informatics and Statistics Centre

for Agriculture and Rural Development, Vietnam Ministry of Agriculture and

Rural Development, Hanoi, Vietnam, Email:phamducthuan42@yahoo.com 4:Statistical Division, Informatics and Statistics

Centre for Agriculture and Rural Development, Vietnam Ministry ofAgriculture and Rural Development, Hanoi, Vietnam, Email:

van@agrifoodconsulting.comPublication date: 2011-06-01

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