DATA…..ANALYSIS….REPORT

Mira K. Desai
Associate Professor
University Department of Extension Education
SNDT Women’s University
Steps in RESEARCH










Formulation of a problem (Assumptions and
Objectives)
Review of Literature
Decisions about Design/Method
Sampling design (Size-Frame-Procedure)
Data Collection (Tools-Techniques-ProceduresExperiences)
Data analysis
Report writing
What is DATA?
Numbers
Information
Statistics

Facts

Figures

Records
DATA is………….INFORMATION



Plural of datum but often used a singular
having quantitative and qualitative
attributes



that has been organised and categorised for
a pre-determined purpose.
Types of Data
PRIMARY





Collected by
researcher first
hand
Demands efforts
and resources
Depends upon the
researcher’s ability
and clarity of
purpose








SECONDARY
Collected by someone
else but used by
researcher second hand
Various sources/forms
Cheaper and quicker
Needs lesser resources
Have to ascertain
accuracy of
content/time/sources/
purpose/methods/
adequacy/ credibility
Data Collection…steps
Construction of tools for data collection
 Decision about techniques of data collection
 Testing the tool/technique by Pilot study or
Pre-testing of tool/technique
 Finalization of tool/technique
 Ascertaining reliability and validity of
tools/techniques to be used for data
collection
 Actual collection of data

Factors influencing decision about data
collection Tool/Technique/Method
Scale and magnitude of the study
 Characteristics of the respondents
 Unit of inquiry and analysis
 Availability of resources:
Money, Time, Human, Technical, Compete
nce
 Field Conditions
 Subject under study
 Expected outcome

Decisions about data collection
Method
Settings: Natural – Contrived/Artificial
 Inquiry: Obstructive/Undisguised –
Unobstructive/Disguised
 Nature: Qualitative – Quantitative
 Structure:
Structured – Semi structured – Unstructured
 Questions: Open ended – Closed ended
 Administration: Human – Mechanical
 Analysis: Pre coded – Not coded

Data comes through….

Tools & Techniques
METHOD

Procedure
Right Question…?!
United Nations conducted a Worldwide survey. The
question asked was:
"Would you please give your honest opinion
about solutions to the food shortage in the rest
of the world?"
The survey was a huge failure.
Africa didn't know what 'food' meant, India didn't
know what 'honest' meant, Europe didn't know what
'shortage' meant, China didn't know what 'opinion'
meant, the Middle East didn't know what 'solution'
meant, South America didn't know what 'please'
meant, And in the USA they didn't know what 'the rest
of the world' meant !!
Good DATA depends upon…
Clarity of purpose/objectives of the study
 Appropriateness of tool/technique
 Sharpness of the tool and abilities of
investigator/researcher in using the
techniques
 Cooperation/rapport with the respondents
 Decisions about utilization at analysis stage

Data Analysis…..Decisions







Type: Qualitative and/or Quantitative
Nature/Mode: Manual or Mechanical
Type of Statistics: Descriptive- Inferential
Type of Analysis: Univariate- BivariateMultivarite- Scores
Presentation: Textual- Tabular-Graphical
Data Analysis…..Steps












Making code book
Coding of data
Creating code-sheets
Data entry
Data Cleaning
ANALYSIS
Interpretation
Presentation
Conclusion














Transcription of data
Organizing data
Creating codes
Classifications
Adding personal
observations
Patterns and themes
New set of data
collection
Generalizations
Data Analysis
DESCRIPTIVE Statistics
 Frequency and Percentages
 Dispersion: Averages, Range, Standard
Deviation,
 Associations: Correlations,
 INFERENTIAL Statistics
Example
Do you have internet on your mobile? If yes, Do
you use internet on mobile? Is yes, how
frequently…..
ASSUMPTIONS:
Everyone has mobile- there may be internet too!!
OBJECTIVES:
To know how many people use internet on move.
DATA:
100 out of 200 people here have internet on their
mobile and 75 of them use it everyday.

Example- Data Interpretation
n=200
150 people have mobiles.
100 of them has Internet on their mobile
75 of them use Internet through mobile everyday.




75% of the people have mobile. (3 in 4 person)
67% mobile owners have Internet on their mobile.
37.5% of all the people use internet on mobile
everyday OR Half (every 2nd) of the mobile
owners use Internet on their mobile everyday.
Research REPORTING Decisions






Why did you undertake research? (AcademicIndustry)
What is the purpose of research? (Degree/PureApplied/solutions)
Who is funding your work? (Funder expectations)
THANKS for TIME & PATIENCE…

drmiradesai@gmail.com
sndtmedia@hotmail.com

Data analysis

  • 1.
    DATA…..ANALYSIS….REPORT Mira K. Desai AssociateProfessor University Department of Extension Education SNDT Women’s University
  • 2.
    Steps in RESEARCH        Formulationof a problem (Assumptions and Objectives) Review of Literature Decisions about Design/Method Sampling design (Size-Frame-Procedure) Data Collection (Tools-Techniques-ProceduresExperiences) Data analysis Report writing
  • 3.
  • 4.
    DATA is………….INFORMATION   Plural ofdatum but often used a singular having quantitative and qualitative attributes  that has been organised and categorised for a pre-determined purpose.
  • 5.
    Types of Data PRIMARY    Collectedby researcher first hand Demands efforts and resources Depends upon the researcher’s ability and clarity of purpose      SECONDARY Collected by someone else but used by researcher second hand Various sources/forms Cheaper and quicker Needs lesser resources Have to ascertain accuracy of content/time/sources/ purpose/methods/ adequacy/ credibility
  • 6.
    Data Collection…steps Construction oftools for data collection  Decision about techniques of data collection  Testing the tool/technique by Pilot study or Pre-testing of tool/technique  Finalization of tool/technique  Ascertaining reliability and validity of tools/techniques to be used for data collection  Actual collection of data 
  • 7.
    Factors influencing decisionabout data collection Tool/Technique/Method Scale and magnitude of the study  Characteristics of the respondents  Unit of inquiry and analysis  Availability of resources: Money, Time, Human, Technical, Compete nce  Field Conditions  Subject under study  Expected outcome 
  • 8.
    Decisions about datacollection Method Settings: Natural – Contrived/Artificial  Inquiry: Obstructive/Undisguised – Unobstructive/Disguised  Nature: Qualitative – Quantitative  Structure: Structured – Semi structured – Unstructured  Questions: Open ended – Closed ended  Administration: Human – Mechanical  Analysis: Pre coded – Not coded 
  • 9.
    Data comes through…. Tools& Techniques METHOD Procedure
  • 10.
    Right Question…?! United Nationsconducted a Worldwide survey. The question asked was: "Would you please give your honest opinion about solutions to the food shortage in the rest of the world?" The survey was a huge failure. Africa didn't know what 'food' meant, India didn't know what 'honest' meant, Europe didn't know what 'shortage' meant, China didn't know what 'opinion' meant, the Middle East didn't know what 'solution' meant, South America didn't know what 'please' meant, And in the USA they didn't know what 'the rest of the world' meant !!
  • 11.
    Good DATA dependsupon… Clarity of purpose/objectives of the study  Appropriateness of tool/technique  Sharpness of the tool and abilities of investigator/researcher in using the techniques  Cooperation/rapport with the respondents  Decisions about utilization at analysis stage 
  • 12.
    Data Analysis…..Decisions      Type: Qualitativeand/or Quantitative Nature/Mode: Manual or Mechanical Type of Statistics: Descriptive- Inferential Type of Analysis: Univariate- BivariateMultivarite- Scores Presentation: Textual- Tabular-Graphical
  • 13.
    Data Analysis…..Steps          Making codebook Coding of data Creating code-sheets Data entry Data Cleaning ANALYSIS Interpretation Presentation Conclusion         Transcription of data Organizing data Creating codes Classifications Adding personal observations Patterns and themes New set of data collection Generalizations
  • 14.
    Data Analysis DESCRIPTIVE Statistics Frequency and Percentages  Dispersion: Averages, Range, Standard Deviation,  Associations: Correlations,  INFERENTIAL Statistics
  • 15.
    Example Do you haveinternet on your mobile? If yes, Do you use internet on mobile? Is yes, how frequently….. ASSUMPTIONS: Everyone has mobile- there may be internet too!! OBJECTIVES: To know how many people use internet on move. DATA: 100 out of 200 people here have internet on their mobile and 75 of them use it everyday. 
  • 16.
    Example- Data Interpretation n=200 150people have mobiles. 100 of them has Internet on their mobile 75 of them use Internet through mobile everyday.    75% of the people have mobile. (3 in 4 person) 67% mobile owners have Internet on their mobile. 37.5% of all the people use internet on mobile everyday OR Half (every 2nd) of the mobile owners use Internet on their mobile everyday.
  • 17.
    Research REPORTING Decisions    Whydid you undertake research? (AcademicIndustry) What is the purpose of research? (Degree/PureApplied/solutions) Who is funding your work? (Funder expectations)
  • 18.
    THANKS for TIME& PATIENCE… drmiradesai@gmail.com sndtmedia@hotmail.com