SlideShare a Scribd company logo
Secondary data is the data that have been already collected by and readily available from
other sources. Such data are cheaper and more quickly obtainable than the primary data and
also may be available when primary data can not be obtained at all.
Advantages of Secondary data
1. It is economical. It saves efforts and expenses.
2. It is time saving.
3. It helps to make primary data collection more specific since with the help of
secondary data, we are able to make out what are the gaps and deficiencies and what
additional information needs to be collected.
4. It helps to improve the understanding of the problem.
5. It provides a basis for comparison for the data that is collected by the researcher.
Disadvantages of Secondary Data
1. Secondary data is something that seldom fits in the framework of the marketing
research factors. Reasons for its non-fitting are:-
a. Unit of secondary data collection-Suppose you want information on
disposable income, but the data is available on gross income. The information
may not be same as we require.
b. Class Boundaries may be different when units are same.
Before 5 Years After 5 Years
2500-5000 5000-6000
5001-7500 6001-7000
7500-10000 7001-10000
c. Thus the data collected earlier is of no use to you.
2. Accuracy of secondary data is not known.
3. Data may be outdated.
Evaluation of Secondary Data
Because of the above mentioned disadvantages of secondary data, we will lead to evaluation
of secondary data. Evaluation means the following four requirements must be satisfied:-
1. Availability- It has to be seen that the kind of data you want is available or not. If it is
not available then you have to go for primary data.
2. Relevance- It should be meeting the requirements of the problem. For this we have
two criterion:-
a. Units of measurement should be the same.
b. Concepts used must be same and currency of data should not be outdated.
3. Accuracy- In order to find how accurate the data is, the following points must be
considered: -
a. Specification and methodology used;
b. Margin of error should be examined;
c. The dependability of the source must be seen.
4. Sufficiency- Adequate data should be available.
Robert W Joselyn has classified the above discussion into eight steps. These eight steps are
sub classified into three categories. He has given a detailed procedure for evaluating
secondary data.
1. Applicability of research objective.
2. Cost of acquisition.
3. Accuracy of data.
http://socialscience.stow.ac.uk/psychology/psych_A/george/primary_secondar
y.htm
Primary data are those that you have collected yourself, whereas secondary data
originate elsewhere. Generally, you will find that you are expected to collect primary
data when using quantitative methods, but that secondary data are more acceptable
when you are using a qualitative method. This is because there are certain common
aspects of qualitative research which involve only secondary data, such as the study
of television or newspaper discourses. If you wanted to understand the nature of the
representation of Romany people on television, you wouldn’t make your own
television programmes! You would use those which exist, and they would form [your]
secondary data (Forshaw, 2000).
A secondary data research project involves the gathering and/or use of
existing data for purposes other than those for which they were originally
collected. These secondary data may be obtained from many sources,
including literature, industry surveys, compilations from computerized
databases and information systems, and computerized or mathematical
models of environmental processes.
Secondary Data
What Is Secondary Data?
o Data may be described as Primary or Secondary
 Primary data - collected by the researcher himself
 Secondary data - collected by others to be "re-used" by the
researcher
What Form Does Secondary Data Take?
o Quantitative Sources
 Published Statistics:
 National Government Sources
 Demographic (Census, Vital Statistics, Cancer
Registrations)
 Administrative (by-product of Government)
 Collected by Govt. Depts. overseen by ONS
(eg. employment, prices, trade, finance)
 Government Surveys (input to Government)
 General Household Survey (GHS)
 Family Expenditure Survey (FES)
 Labour Force Survey (LFS)
 Family Resources Survey (FRS)
 Omnibus Survey
 Local Government Sources
 Planning Documents
 Trends Documents (eg former Strathclyde Social
Trends and Economic Trends)
 Other Sources
 Firms & Trade Associations eg Society of Motot
Manufacturers & Traders (SMMT)
 Market & Opinion Research eg Gallup, NOP,
SCPR System 3
 Trade Unions, TUC, STUC
 Professional Bodies eg CIPFA (Chartered Institute
of Public Finance & Accountancy) provides a
Statistical Information Service re Local
Government Statistics
 Political Parties
 Voluntary & Charitable Bodies eg Low Pay Unit,
SCF (Save the Children Fund), Rowntree
Foundation
 Academic & Research Institutes eg
 Micro-Social Change Research Centre
(MSRC) at Essex Uni
 National Institute for Economic & Social
Research (NIESR)
 Institute for Fiscal Studies (IFS)
 International Sources
 EU, OECD, World Bank, IMF
 Non-Published / Electronic Sources
 Data Archives eg the Data Archive At Essex
 Data Sub-Setting Service On Tape, Disk, Postal
Or Via Janet
 On-Line Access To National Computing Centres
 MIMAS (Manchester Information & Associated
Services)
 EDINA (Edinburgh)
 International Sources on Internet & Web
o Qualitative Sources
/ Sources for Qualitative Research:
 Biographies - subjective interpretation involved
 Diaries - more spontaneous, less distorted by memory lapses
 Memoirs - benefit/problem of hindsight
 Letters - reveal interactions
 Newspapers - public interest & opinion
 Novels & Literature In General - eg Atkinson's tribute to
usefulness of Gordon's "Dr Novels"; McLelland's study of
achievement motivation in different cultures via children's stories
& folktales
 Handbooks, Policy Statements, Planning Documents, Reports,
Historical & Official Documents (Hansard, Royal Commission
reports) etc. n.b Marx's use of Factory Inspectors reports in
developing his theories of the labour process
Ways of Using Secondary Sources
o Exploratory phase - getting ideas
o Design Phase - definitions & sampling frames, question wording
o Supplement to Main Research
 - Re-Enforcement &/Or Comparison
o Main Mode of Research
 - Direct Data Collection Impossible
 - Or Costly & Time Consuming
Limitations of Secondary Data
o Collected For A Different Purpose
o Problem of Definitions
o Problem of Comparability Over Time
o Lack of Awareness of Sources of Error/Bias
o Has the Data Been "Massaged"?
o What Do The Statistics Really Mean?
 Eg. Health, Crime, Unemployment
o Limitations of Survey Data
 Representativeness
 Validity of Responses
o Limitations of Documents
 Documents "Construct" As Well As Report Social Reality
How to Search & Use Secondary Sources?
o Documents - Bibliographic Skills, Use of Keywords, Boolean Operators
o Published Statistics
 Guide to Official Statistics
 Digests & Abstracts
 Primary Publication
o Electronic Sources
 Biron
 Gateways - SOSIG, BUBL
 Search Engines - Infoseek, Alta Vista, Webcrawler etc.
SOURCE: RMS - the Research Methods Server in the Division of Social Sciences,
School of Law and Social Sciences, Glasgow Caledonian University, Glasgow.
Forshaw, M (2000) Your Undergraduate Psychology Project: A BPS Guide Blackwell
Publishing

More Related Content

What's hot

Team 6 Assignment
Team 6 AssignmentTeam 6 Assignment
Team 6 Assignment
Annie Thomas
 
Finding news guide feb 2011
Finding news guide feb 2011Finding news guide feb 2011
Finding news guide feb 2011
Sam Aston
 
Biography Information Resources
Biography Information ResourcesBiography Information Resources
Biography Information Resources
annbee
 
Bibliometrix Seminar
Bibliometrix SeminarBibliometrix Seminar
Bibliometrix Seminar
Massimo Aria
 
Federal Social Statistics
Federal Social StatisticsFederal Social Statistics
Federal Social Statistics
kingv
 
Scopus exercises
Scopus exercisesScopus exercises
Scopus exercises
Sam Aston
 
LIS 60601 BI Presentation - Fed Gov\'t Stats
LIS 60601 BI Presentation - Fed Gov\'t StatsLIS 60601 BI Presentation - Fed Gov\'t Stats
LIS 60601 BI Presentation - Fed Gov\'t Stats
Ellen Armstrong
 
Research Data Management
Research  Data ManagementResearch  Data Management
Research Data Management
Mahmoud91Tx
 
Finding news feb 2011
Finding news feb 2011Finding news feb 2011
Finding news feb 2011
Sam Aston
 
Příklad bibliometrické zprávy
Příklad bibliometrické zprávyPříklad bibliometrické zprávy
Příklad bibliometrické zprávy
MEYS, MŠMT in Czech
 
Data journalism, city uni 3 march
Data journalism, city uni   3 marchData journalism, city uni   3 march
Data journalism, city uni 3 march
Patrick Smith
 
How to handle government related questions.
How to handle government related questions.How to handle government related questions.
How to handle government related questions.
Kyle Guzik
 
Management Accounting Hons Library Training
Management Accounting Hons Library Training Management Accounting Hons Library Training
Management Accounting Hons Library Training
pvhead123
 
Quality Indices
Quality IndicesQuality Indices
Quality Indices
Dr. Chetan Bhatt
 

What's hot (15)

Team 6 Assignment
Team 6 AssignmentTeam 6 Assignment
Team 6 Assignment
 
Finding news guide feb 2011
Finding news guide feb 2011Finding news guide feb 2011
Finding news guide feb 2011
 
 
Biography Information Resources
Biography Information ResourcesBiography Information Resources
Biography Information Resources
 
Bibliometrix Seminar
Bibliometrix SeminarBibliometrix Seminar
Bibliometrix Seminar
 
Federal Social Statistics
Federal Social StatisticsFederal Social Statistics
Federal Social Statistics
 
Scopus exercises
Scopus exercisesScopus exercises
Scopus exercises
 
LIS 60601 BI Presentation - Fed Gov\'t Stats
LIS 60601 BI Presentation - Fed Gov\'t StatsLIS 60601 BI Presentation - Fed Gov\'t Stats
LIS 60601 BI Presentation - Fed Gov\'t Stats
 
Research Data Management
Research  Data ManagementResearch  Data Management
Research Data Management
 
Finding news feb 2011
Finding news feb 2011Finding news feb 2011
Finding news feb 2011
 
Příklad bibliometrické zprávy
Příklad bibliometrické zprávyPříklad bibliometrické zprávy
Příklad bibliometrické zprávy
 
Data journalism, city uni 3 march
Data journalism, city uni   3 marchData journalism, city uni   3 march
Data journalism, city uni 3 march
 
How to handle government related questions.
How to handle government related questions.How to handle government related questions.
How to handle government related questions.
 
Management Accounting Hons Library Training
Management Accounting Hons Library Training Management Accounting Hons Library Training
Management Accounting Hons Library Training
 
Quality Indices
Quality IndicesQuality Indices
Quality Indices
 

Viewers also liked

MSM 2011 keynote
MSM 2011 keynoteMSM 2011 keynote
MSM 2011 keynote
msm2011socialcom
 
Myyräekinokokki ja luonnontuotteiden turvallisuus
Myyräekinokokki ja luonnontuotteiden turvallisuusMyyräekinokokki ja luonnontuotteiden turvallisuus
Myyräekinokokki ja luonnontuotteiden turvallisuus
Matleena Pulkkinen
 
Härkäniemen tuvat 10.10.2011
Härkäniemen tuvat 10.10.2011Härkäniemen tuvat 10.10.2011
Härkäniemen tuvat 10.10.2011
Matleena Pulkkinen
 
Dingo Bells
Dingo BellsDingo Bells
Dingo Bells
Rafael Gloria
 
Libya and its influence
Libya and its influenceLibya and its influence
Libya and its influence
Huma Chaudhry
 
Global assignment individual poverty_fight
Global assignment individual poverty_fightGlobal assignment individual poverty_fight
Global assignment individual poverty_fight
Huma Chaudhry
 
Chapter 19: Unexpected Pregnancy
Chapter 19: Unexpected PregnancyChapter 19: Unexpected Pregnancy
Chapter 19: Unexpected Pregnancy
Alyssa Reid
 

Viewers also liked (7)

MSM 2011 keynote
MSM 2011 keynoteMSM 2011 keynote
MSM 2011 keynote
 
Myyräekinokokki ja luonnontuotteiden turvallisuus
Myyräekinokokki ja luonnontuotteiden turvallisuusMyyräekinokokki ja luonnontuotteiden turvallisuus
Myyräekinokokki ja luonnontuotteiden turvallisuus
 
Härkäniemen tuvat 10.10.2011
Härkäniemen tuvat 10.10.2011Härkäniemen tuvat 10.10.2011
Härkäniemen tuvat 10.10.2011
 
Dingo Bells
Dingo BellsDingo Bells
Dingo Bells
 
Libya and its influence
Libya and its influenceLibya and its influence
Libya and its influence
 
Global assignment individual poverty_fight
Global assignment individual poverty_fightGlobal assignment individual poverty_fight
Global assignment individual poverty_fight
 
Chapter 19: Unexpected Pregnancy
Chapter 19: Unexpected PregnancyChapter 19: Unexpected Pregnancy
Chapter 19: Unexpected Pregnancy
 

Similar to S2

using_secondary and primary data
using_secondary and primary datausing_secondary and primary data
using_secondary and primary data
AravindS193
 
S4 pn
S4 pnS4 pn
Methods of data collection
Methods of data collectionMethods of data collection
Methods of data collection
Chintan Trivedi
 
Research design ppt (1)
Research design ppt  (1)Research design ppt  (1)
Research design ppt (1)
Dr Vikas Gautam
 
SOC2002 Lecture 6
SOC2002 Lecture 6SOC2002 Lecture 6
SOC2002 Lecture 6
Bonnie Green
 
Primary data and secondary data
Primary data and secondary dataPrimary data and secondary data
Primary data and secondary data
Sanjay Basukala
 
Final ppt sec.data.coll
Final ppt sec.data.collFinal ppt sec.data.coll
Final ppt sec.data.coll
Ram Sonawane
 
Data collection methods
Data collection methodsData collection methods
Data collection methods
Sourabh Modgil
 
Data collection methods
Data collection methodsData collection methods
Data collection methods
ashima_sodhi
 
Methods of data collection
Methods of data collectionMethods of data collection
Methods of data collection
Binty Agarwal
 
Methods of data collection
Methods of data collectionMethods of data collection
Methods of data collection
Binty Agarwal
 
Statistics
Statistics Statistics
Statistics
Jasminekharel
 
Marketing research ch 4_malhotra
Marketing research ch 4_malhotraMarketing research ch 4_malhotra
Marketing research ch 4_malhotra
Jamil Ahmed AKASH
 
Accessing Secondary Data A Literature Review
Accessing Secondary Data   A Literature ReviewAccessing Secondary Data   A Literature Review
Accessing Secondary Data A Literature Review
Gina Rizzo
 
Researchpe-5.pptx
Researchpe-5.pptxResearchpe-5.pptx
Researchpe-5.pptx
Parwez17
 
Aed1222 lesson 1 and 3
Aed1222 lesson 1 and 3Aed1222 lesson 1 and 3
Aed1222 lesson 1 and 3
nurun2010
 
( research mythology)
( research  mythology)( research  mythology)
Secondary data collection.mjm
Secondary data collection.mjmSecondary data collection.mjm
Secondary data collection.mjm
manjunath
 
SEEMA KUMARI BPT 4th year secondary data.pptx
SEEMA KUMARI  BPT 4th year secondary data.pptxSEEMA KUMARI  BPT 4th year secondary data.pptx
SEEMA KUMARI BPT 4th year secondary data.pptx
AlkaKumari74
 
unit 2.3.ppt
unit 2.3.pptunit 2.3.ppt
unit 2.3.ppt
Sumit Kumar
 

Similar to S2 (20)

using_secondary and primary data
using_secondary and primary datausing_secondary and primary data
using_secondary and primary data
 
S4 pn
S4 pnS4 pn
S4 pn
 
Methods of data collection
Methods of data collectionMethods of data collection
Methods of data collection
 
Research design ppt (1)
Research design ppt  (1)Research design ppt  (1)
Research design ppt (1)
 
SOC2002 Lecture 6
SOC2002 Lecture 6SOC2002 Lecture 6
SOC2002 Lecture 6
 
Primary data and secondary data
Primary data and secondary dataPrimary data and secondary data
Primary data and secondary data
 
Final ppt sec.data.coll
Final ppt sec.data.collFinal ppt sec.data.coll
Final ppt sec.data.coll
 
Data collection methods
Data collection methodsData collection methods
Data collection methods
 
Data collection methods
Data collection methodsData collection methods
Data collection methods
 
Methods of data collection
Methods of data collectionMethods of data collection
Methods of data collection
 
Methods of data collection
Methods of data collectionMethods of data collection
Methods of data collection
 
Statistics
Statistics Statistics
Statistics
 
Marketing research ch 4_malhotra
Marketing research ch 4_malhotraMarketing research ch 4_malhotra
Marketing research ch 4_malhotra
 
Accessing Secondary Data A Literature Review
Accessing Secondary Data   A Literature ReviewAccessing Secondary Data   A Literature Review
Accessing Secondary Data A Literature Review
 
Researchpe-5.pptx
Researchpe-5.pptxResearchpe-5.pptx
Researchpe-5.pptx
 
Aed1222 lesson 1 and 3
Aed1222 lesson 1 and 3Aed1222 lesson 1 and 3
Aed1222 lesson 1 and 3
 
( research mythology)
( research  mythology)( research  mythology)
( research mythology)
 
Secondary data collection.mjm
Secondary data collection.mjmSecondary data collection.mjm
Secondary data collection.mjm
 
SEEMA KUMARI BPT 4th year secondary data.pptx
SEEMA KUMARI  BPT 4th year secondary data.pptxSEEMA KUMARI  BPT 4th year secondary data.pptx
SEEMA KUMARI BPT 4th year secondary data.pptx
 
unit 2.3.ppt
unit 2.3.pptunit 2.3.ppt
unit 2.3.ppt
 

Recently uploaded

“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”
Claudio Di Ciccio
 
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success StoryDriving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Safe Software
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Zilliz
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
Daiki Mogmet Ito
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
名前 です男
 
June Patch Tuesday
June Patch TuesdayJune Patch Tuesday
June Patch Tuesday
Ivanti
 
Removing Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software FuzzingRemoving Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software Fuzzing
Aftab Hussain
 
Serial Arm Control in Real Time Presentation
Serial Arm Control in Real Time PresentationSerial Arm Control in Real Time Presentation
Serial Arm Control in Real Time Presentation
tolgahangng
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
Wouter Lemaire
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
panagenda
 
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalizationFull-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
Zilliz
 
Infrastructure Challenges in Scaling RAG with Custom AI models
Infrastructure Challenges in Scaling RAG with Custom AI modelsInfrastructure Challenges in Scaling RAG with Custom AI models
Infrastructure Challenges in Scaling RAG with Custom AI models
Zilliz
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
Octavian Nadolu
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
shyamraj55
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
Matthew Sinclair
 
Microsoft - Power Platform_G.Aspiotis.pdf
Microsoft - Power Platform_G.Aspiotis.pdfMicrosoft - Power Platform_G.Aspiotis.pdf
Microsoft - Power Platform_G.Aspiotis.pdf
Uni Systems S.M.S.A.
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Pixlogix Infotech
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
akankshawande
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
Zilliz
 

Recently uploaded (20)

“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”
 
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success StoryDriving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
 
June Patch Tuesday
June Patch TuesdayJune Patch Tuesday
June Patch Tuesday
 
Removing Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software FuzzingRemoving Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software Fuzzing
 
Serial Arm Control in Real Time Presentation
Serial Arm Control in Real Time PresentationSerial Arm Control in Real Time Presentation
Serial Arm Control in Real Time Presentation
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
 
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalizationFull-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
 
Infrastructure Challenges in Scaling RAG with Custom AI models
Infrastructure Challenges in Scaling RAG with Custom AI modelsInfrastructure Challenges in Scaling RAG with Custom AI models
Infrastructure Challenges in Scaling RAG with Custom AI models
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
 
Microsoft - Power Platform_G.Aspiotis.pdf
Microsoft - Power Platform_G.Aspiotis.pdfMicrosoft - Power Platform_G.Aspiotis.pdf
Microsoft - Power Platform_G.Aspiotis.pdf
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
 

S2

  • 1. Secondary data is the data that have been already collected by and readily available from other sources. Such data are cheaper and more quickly obtainable than the primary data and also may be available when primary data can not be obtained at all. Advantages of Secondary data 1. It is economical. It saves efforts and expenses. 2. It is time saving. 3. It helps to make primary data collection more specific since with the help of secondary data, we are able to make out what are the gaps and deficiencies and what additional information needs to be collected. 4. It helps to improve the understanding of the problem. 5. It provides a basis for comparison for the data that is collected by the researcher. Disadvantages of Secondary Data 1. Secondary data is something that seldom fits in the framework of the marketing research factors. Reasons for its non-fitting are:- a. Unit of secondary data collection-Suppose you want information on disposable income, but the data is available on gross income. The information may not be same as we require. b. Class Boundaries may be different when units are same. Before 5 Years After 5 Years 2500-5000 5000-6000 5001-7500 6001-7000 7500-10000 7001-10000 c. Thus the data collected earlier is of no use to you. 2. Accuracy of secondary data is not known. 3. Data may be outdated. Evaluation of Secondary Data Because of the above mentioned disadvantages of secondary data, we will lead to evaluation of secondary data. Evaluation means the following four requirements must be satisfied:- 1. Availability- It has to be seen that the kind of data you want is available or not. If it is not available then you have to go for primary data. 2. Relevance- It should be meeting the requirements of the problem. For this we have two criterion:- a. Units of measurement should be the same. b. Concepts used must be same and currency of data should not be outdated. 3. Accuracy- In order to find how accurate the data is, the following points must be considered: - a. Specification and methodology used; b. Margin of error should be examined; c. The dependability of the source must be seen.
  • 2. 4. Sufficiency- Adequate data should be available. Robert W Joselyn has classified the above discussion into eight steps. These eight steps are sub classified into three categories. He has given a detailed procedure for evaluating secondary data. 1. Applicability of research objective. 2. Cost of acquisition. 3. Accuracy of data. http://socialscience.stow.ac.uk/psychology/psych_A/george/primary_secondar y.htm Primary data are those that you have collected yourself, whereas secondary data originate elsewhere. Generally, you will find that you are expected to collect primary data when using quantitative methods, but that secondary data are more acceptable when you are using a qualitative method. This is because there are certain common aspects of qualitative research which involve only secondary data, such as the study of television or newspaper discourses. If you wanted to understand the nature of the representation of Romany people on television, you wouldn’t make your own television programmes! You would use those which exist, and they would form [your] secondary data (Forshaw, 2000). A secondary data research project involves the gathering and/or use of existing data for purposes other than those for which they were originally collected. These secondary data may be obtained from many sources, including literature, industry surveys, compilations from computerized databases and information systems, and computerized or mathematical models of environmental processes. Secondary Data What Is Secondary Data? o Data may be described as Primary or Secondary  Primary data - collected by the researcher himself  Secondary data - collected by others to be "re-used" by the researcher What Form Does Secondary Data Take? o Quantitative Sources  Published Statistics:  National Government Sources  Demographic (Census, Vital Statistics, Cancer Registrations)  Administrative (by-product of Government)  Collected by Govt. Depts. overseen by ONS (eg. employment, prices, trade, finance)  Government Surveys (input to Government)
  • 3.  General Household Survey (GHS)  Family Expenditure Survey (FES)  Labour Force Survey (LFS)  Family Resources Survey (FRS)  Omnibus Survey  Local Government Sources  Planning Documents  Trends Documents (eg former Strathclyde Social Trends and Economic Trends)  Other Sources  Firms & Trade Associations eg Society of Motot Manufacturers & Traders (SMMT)  Market & Opinion Research eg Gallup, NOP, SCPR System 3  Trade Unions, TUC, STUC  Professional Bodies eg CIPFA (Chartered Institute of Public Finance & Accountancy) provides a Statistical Information Service re Local Government Statistics  Political Parties  Voluntary & Charitable Bodies eg Low Pay Unit, SCF (Save the Children Fund), Rowntree Foundation  Academic & Research Institutes eg  Micro-Social Change Research Centre (MSRC) at Essex Uni  National Institute for Economic & Social Research (NIESR)  Institute for Fiscal Studies (IFS)  International Sources  EU, OECD, World Bank, IMF  Non-Published / Electronic Sources  Data Archives eg the Data Archive At Essex  Data Sub-Setting Service On Tape, Disk, Postal Or Via Janet  On-Line Access To National Computing Centres  MIMAS (Manchester Information & Associated Services)  EDINA (Edinburgh)  International Sources on Internet & Web o Qualitative Sources / Sources for Qualitative Research:  Biographies - subjective interpretation involved  Diaries - more spontaneous, less distorted by memory lapses  Memoirs - benefit/problem of hindsight
  • 4.  Letters - reveal interactions  Newspapers - public interest & opinion  Novels & Literature In General - eg Atkinson's tribute to usefulness of Gordon's "Dr Novels"; McLelland's study of achievement motivation in different cultures via children's stories & folktales  Handbooks, Policy Statements, Planning Documents, Reports, Historical & Official Documents (Hansard, Royal Commission reports) etc. n.b Marx's use of Factory Inspectors reports in developing his theories of the labour process Ways of Using Secondary Sources o Exploratory phase - getting ideas o Design Phase - definitions & sampling frames, question wording o Supplement to Main Research  - Re-Enforcement &/Or Comparison o Main Mode of Research  - Direct Data Collection Impossible  - Or Costly & Time Consuming Limitations of Secondary Data o Collected For A Different Purpose o Problem of Definitions o Problem of Comparability Over Time o Lack of Awareness of Sources of Error/Bias o Has the Data Been "Massaged"? o What Do The Statistics Really Mean?  Eg. Health, Crime, Unemployment o Limitations of Survey Data  Representativeness  Validity of Responses o Limitations of Documents  Documents "Construct" As Well As Report Social Reality How to Search & Use Secondary Sources? o Documents - Bibliographic Skills, Use of Keywords, Boolean Operators o Published Statistics  Guide to Official Statistics  Digests & Abstracts  Primary Publication o Electronic Sources  Biron  Gateways - SOSIG, BUBL  Search Engines - Infoseek, Alta Vista, Webcrawler etc. SOURCE: RMS - the Research Methods Server in the Division of Social Sciences, School of Law and Social Sciences, Glasgow Caledonian University, Glasgow.
  • 5. Forshaw, M (2000) Your Undergraduate Psychology Project: A BPS Guide Blackwell Publishing