O slideshow foi denunciado.
Utilizamos seu perfil e dados de atividades no LinkedIn para personalizar e exibir anúncios mais relevantes. Altere suas preferências de anúncios quando desejar.
Data Collection, Assessment of
Qualitative Data, Data Processing:
Key Issues
Bikash Sapkota
B. Optometry
Institute of Medi...
• Introduction to data
• Classification of data
• Collection of data
• Methods of data collection
• Assessment of qualitat...
What is data?
 Data are observations or evidences about the social world
 Data, the plural of datum, can be quantitative...
 The terms 'data' and 'information' are used interchangeably
 However the terms have distinct meanings
Data
Facts, event...
 The research studies in behavioral science are mainly
concerned with the characteristics or traits
 Thus, tools are adm...
Nature of Data
1.Qualitative Data or Attributes
The characteristics or traits for which numerical value
can not be assigne...
Constants
A constant is all characteristic or condition that is the same for
all the observed units or sample subjects of ...
Variables
1. Continuous variables
 A characteristic whose observation can take any values over a
particular range
 It ca...
Attribute vs. Variable
Attribute Variable
 A category of a characteristic,
to which a subject either
belongs or does not ...
Qualitative Data
 In such data there is no notion of magnitude of size of the
characteristic
 They are just categorized
...
Quantitative Data
 Anything that can be expressed as a number, or quantity or
magnitude
 Describes characteristics in te...
Measurement Scale
 The choice of appropriate statistical technique depends
upon the type of data in question
Qualitative
...
Nominal Scale
 The least precise or crude of the 4 basic scales of
measurement
 Implies the classification of an item in...
Ordinal Scale
 The ordinal scale is more precise scale than the nominal
scale
 The variables has been categorized or lev...
Interval Scale
 The interval scale is more precise and refined scale than
nominal and ordinal scales
 This scale has all...
Ratio Scale
 It has the same properties as an interval scale as well as a
true or absolute zero value
 The ratio scale n...
 Process of systematic gathering of data for a particular
purpose from various sources, that has been systematically
obse...
 To obtain information
 To keep on record
 To make decisions about important issues
 To pass information onto others
...
Data collection is an extremely important part of any
research because the conclusions of a study are
based on what the da...
Nature, scope & objective of the enquiry
Sources of information
Availability of fund
Techniques of data collection
Av...
Example:
Documents
Creative works
Interviews
Man-made materials
Surveys
Example:
Unpublished thesis and
dissertations
Manu...
Internal sources of Data
o Many institutions and
departments have information
about their regular functions ,
for their ow...
 Data collected by investigator from personal experimental
studies for a specific research goal is called primary data
 ...
Demerits
Evaluated cost
Time consuming
More number of resources
are required
Inaccurate feedback
Required lot of skill wit...
Interview (direct/indirect)
Schedule
Questionnaires survey
Focus group discussion (FGD)
Community forums and public h...
 The data is collected by the investigator personally, he/she
must be a keen observer
 He/she asks or cross-examines the...
Direct personal observation is adopted in the following cases
Where greater accuracy is needed
Where the field of enquir...
Merits
Original data
True and reliable data
Encouraging response
because of personal
approach
A high degree of accurac...
 The investigator approaches the witness or third parties,
who are in touch with the informant
 The enumerator interview...
 It is more suitable when the area to be studied is large
 It is used when direct information cannot be obtained
 This ...
Merits
 Simple and convenient
 Saves time, money and labor
 Useful in investigation of a large area
 Adequate informat...
 The local agents or correspondents will be appointed, they
collect the information and transmit it to the office or pers...
Merits
Demerits
 Extensive information can be had
 It is the most cheap and economical method
 Speedy information is po...
 The questionnaires is sent to the respondents, there are blank
spaces for answers
 A covering letter is also sent along...
Merits
 Of all the methods, the mailed questionnaire is the most
economical
 It can be widely used, when the area of inv...
 Very similar to the questionnaire method
 The main difference is that a schedule is filled by the
enumerator who is spe...
 A detailed study of geographical area to gather data,
attitudes, impressions, opinions, satisfaction level etc., by
poll...
Merits
Cover large population
Less expensive
Information is accurate
Demerits
On small scale survey
avoided
Time consuming...
 It is the method of comprehensive study of social unit which
may be a person, a family, an institution, an organization ...
 Useful to further explore a topic, providing a broader
understanding of why the target group may behave or
think in a pa...
Merits
 Useful when exploring cultural values and health beliefs
 Can be used to explore complex issues
 Can be used to...
 Application and combination of several research methods in the
study of the same phenomenon
 Researchers can hope to ov...
 Secondary data are those data which have been already
collected and analysed by some earlier agency for its own
use and ...
Various governmental, international and local agencies
publish statistical data, and chief among them are:
 International...
 Publications of Research Institutions: Nepal Development
Research Institute, Nepalese Journal of Ophthalmology etc.
publ...
 Records maintained by various government and private
offices
 Researches carried out by individual research scholars in...
Before using the secondary data, the investigators should
consider the following factors:
Precautions in the use of Second...
Reliability of data – may be tested by checking:
Who collected the data?
What were the sources of the data?
Was the dat...
Primary data
o Real time data
o Sure about sources of data
o Help to give results/ finding
o Costly and time consuming
pro...
 The characteristics or traits for which numerical value can
not be assigned, are called qualitative data (attributes)
e....
 Classification of Qualitative data
Qualitative
Data
Geographical
Classification
Chronological
Classification
Qualitative...
Tabulation of Qualitative Data
 Qualitative data values can be organized by a frequency
distribution
 A frequency distri...
Frequency Table
 A simple data set is: cataract, cataract, keratoconus, glaucoma,
glaucoma, cataract, glaucoma, cataract
...
What Is A Relative Frequency?
 The relative frequencies are the proportions (or percents)
of the observations out of the ...
Relative Frequency Table
 A relative frequency table for this qualitative data is
 A relative frequency table can also b...
 Graphical representation Of Qualitative Data
Bar Diagram
Pie or Sector
Diagram
Line Diagram
Pictogram
Map Diagram or
Car...
Data Processing
 The data, after collection, has to be prepared for analysis
 Collected data is raw and it must undergo some processing
...
 Checking the questionnaires and schedules
 Reduction of mass data to manageable proportion
 Sum up the materials so as...
1. Manual Data Processing
 Involves human intervention
 Implies many chances for errors, such as delays in data
capture,...
2. Mechanical Data Processing
 Different calculations and processing are performed
using mechanical machines like calcula...
3. Electronic Data Processing
 Processing of data by use of computer and its programs
Types of Data Processing
4. Real Time Processing
 There is a continual input, process and output of data
 Data has to be processed in a small sti...
5. Batch Processing
 In a batch processing group of transactions collected over a
period of time is collected, entered, p...
QUESTIONNAIRE
CHECKING EDITING CODING CLASSIFICATION
TABULATION
GRAPHICAL
REPRESENTATION
DATA CLEANINGDATA ADJUSTING
The p...
 When the data is collected through questionnaires, the first
steps of data process is to check the questionnaires if the...
 Process of examining the data collected in
questionnaires/schedules
to detect errors and omissions
to correct these wh...
 Editor is responsible for seeing that the data are;
Accurate as possible
Consistent with other facts secured
Uniforml...
• Data form complete
• Free of bias, errors,
inconsistency and dishonesty
Editing for quality
• Modification to facilitate...
 To gather information
 To make data relevant and appropriate for analysis
 To find errors and modify them
 To ensures...
 Process of assigning numerals or other symbols to answers so
that responses can be put into limited number of categories...
72
• A codebook contains coding instructions and the necessary
information about variables in the data set
• A codebook ge...
 To organize data code
 To form structure for coding
 For interpretation of data
 For conclusions of data coded
 To t...
 The process of arranging the primary data in a definite
pattern and presenting it in a systematic way
 The crude data o...
 The classified data is more easily understood
 It presents the facts into a simpler form
 It facilitates quick compari...
Qualitative classification
Geographical classification
Chronological classification
Qualitative classification
Quantitativ...
Geographical Classification
 Data are classified by location of occurrence (i.e. area, region)
eg cataract pts. district ...
Qualitative classification (Classification according to attributes)
 Data are classified according to some quality such a...
 Process of systematic organization and recording of
long series of data for further analysis and
interpretation into row...
 It presents an overall view of findings in a simpler way
 To identify trends
 It displays relationships in a comparabl...
Graphical Representation
 Graphs help to understand the data easily
 A single picture is worth a thousand words-so goes ...
Graphical Representation
Advantages
 It is easier to read
 Can show relationship between 2 or more sets of
observations ...
Presentation of Qualitative data
1. Bar Diagram
• Consists of equally spaced vertical (or horizontal)
rectangular bars of ...
Graphical Representation
0
100
200
300
400
BPH MBBS B.Optom B.Pharma
NO.OFSTUDENTS
HEALTH PROGRAM
Health Program at IOM
Si...
Graphical Representation
2. Pie Chart
• Circular diagram divided into segments and each
segment represent frequency in a c...
Graphical Representation
Production of health manpower
yearly
Pictogram
Line diagram
Cartogram
Graphical Representation
Presentation of Quantitative Data
1.Histogram
• Graphical representation of a set of contiguously...
Graphical Representation
Frequency Polygon
Frequency Curve
Scatter Diagram Time Plot
Graphical Representation
Stem-leaf Display
Box-and-whisker Plot
 Includes consistency checks and treatment of missing
responses
 Although preliminary consistency checks have been made
...
 If any correction needs to be done for the statistical
analysis, the data is adjusted accordingly
Data Adjusting
 Data ...
• Biostatistics by Prem P. Panta
• Fundamentals of Research Methodology and
Statistics by Yogesh k. Singh
• Research Desig...
Próximos SlideShares
Carregando em…5
×

Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Qualitative & Quantitative Data, Data Processing (healthkura.com)

22.469 visualizações

Publicada em

Dear viewers Check Out my other piece of works at___ https://healthkura.com

Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Assessment of Qualitative Data, Qualitative & Quantitative Data, Data Processing


Presentation Contents:
- Introduction to data
- Classification of data
- Collection of data
- Methods of data collection
- Assessment of qualitative data
- Processing of data
- Editing
- Coding
- Tabulation
- Graphical representation

If anyone is really interested about research related topics particularly on data collection, this presentation will be the best reference.

For Further Reading
- Biostatistics by Prem P. Panta
- Fundamentals of Research Methodology and Statistics by Yogesh k. Singh
- Research Design by J. W. Creswell
- Internet

Publicada em: Educação
  • Entre para ver os comentários

Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Qualitative & Quantitative Data, Data Processing (healthkura.com)

  1. 1. Data Collection, Assessment of Qualitative Data, Data Processing: Key Issues Bikash Sapkota B. Optometry Institute of Medicine, TU, Nepal
  2. 2. • Introduction to data • Classification of data • Collection of data • Methods of data collection • Assessment of qualitative data • Processing of data - Editing - Coding - Tabulation - Graphical representation Presentation Layout
  3. 3. What is data?  Data are observations or evidences about the social world  Data, the plural of datum, can be quantitative or qualitative in nature  ‘data is produced, not given’; that is, researchers choose what to call data, it is not just ‘there’ to be ‘found’. (Marsh 1988) - The Sage Dictionary of Social Research Methods
  4. 4.  The terms 'data' and 'information' are used interchangeably  However the terms have distinct meanings Data Facts, events, transactions which have been recorded Input raw materials from which information is processed Information Data that have been produced in such a way as to be useful to the recipient Basic data are processed in some way to form information Data & Information
  5. 5.  The research studies in behavioral science are mainly concerned with the characteristics or traits  Thus, tools are administered to quantify these characteristics - but all traits or characteristics can not be quantified The data can be classified into two broad categories: Data Qualitative Data or Attributes Quantitative Data or Variables Nature of Data
  6. 6. Nature of Data 1.Qualitative Data or Attributes The characteristics or traits for which numerical value can not be assigned, are called attributes e.g. gender, motivation, etc. 2. Quantitative Data or Variables The characteristics or traits for which numerical value can be assigned, are called variables e.g. height, weight etc.
  7. 7. Constants A constant is all characteristic or condition that is the same for all the observed units or sample subjects of a study Variables The characteristic or the trait in the behavioral science which can be quantified is termed as variable Variables Continuous variables Discrete variables
  8. 8. Variables 1. Continuous variables  A characteristic whose observation can take any values over a particular range  It can assure either fractional or integral values  E.g. wt. of children in kg, height of pt. 2. Discrete variables  Are those on the other hand, which exist only in units not the fractional value (usually units of one)  E.g. No. of cataract pts. in a village, WBC count
  9. 9. Attribute vs. Variable Attribute Variable  A category of a characteristic, to which a subject either belongs or does not belong or property that a subject either possesses or does not possess  The attributes are becoming sick, describing blood group etc.  Variable describes a characteristic in terms of a numerical value, which is expressed in units of measurements  The variables are height, weight, blood pressure, age of pts. etc.
  10. 10. Qualitative Data  In such data there is no notion of magnitude of size of the characteristic  They are just categorized  The data are classified by counting the individuals having the same characteristics or attribute and not by measurement  For examples: Gender: male/female Disease: present/absent Smoke: smoking/not smoking  These data can be measured in nominal and ordinal scales
  11. 11. Quantitative Data  Anything that can be expressed as a number, or quantity or magnitude  Describes characteristics in term of a numerical value, which are expressed in units of measurements  E.g. level of hemoglobin in the blood, no. of glaucoma pts., intra ocular pressure, weight, etc.  Quantitative observations: as each individual is represented by a number  These data can be measured in interval and ratio scales
  12. 12. Measurement Scale  The choice of appropriate statistical technique depends upon the type of data in question Qualitative Data • Nominal Scale • Ordinal Scale Quantitative Data • Interval Scale • Ratio Scale
  13. 13. Nominal Scale  The least precise or crude of the 4 basic scales of measurement  Implies the classification of an item into 2 or more categories without any extent or magnitude  There is no particular order assigned to them  The frequency or numbers are used to give a name to something that may be used for determining per cent, mode Eg. boys and girls; pass and fail; rural and urban
  14. 14. Ordinal Scale  The ordinal scale is more precise scale than the nominal scale  The variables has been categorized or leveled with meaningful natural order  But there is no information about the interval Eg. Pain: none, mild, moderate, severe
  15. 15. Interval Scale  The interval scale is more precise and refined scale than nominal and ordinal scales  This scale has all the characteristics and relationship of the ordinal scale, besides which distances between any two numbers on the scale are known  The size of interval between two observations can be measured Eg. The temperature of a body
  16. 16. Ratio Scale  It has the same properties as an interval scale as well as a true or absolute zero value  The ratio scale numerals have the qualities of real numbers, and can be added, subtracted, multiplied or divided Eg. Mean systolic BP
  17. 17.  Process of systematic gathering of data for a particular purpose from various sources, that has been systematically observed, recorded, organized  It is the first step of statistical study  There are several ways of collecting data  The choice of procedures usually depends on the objectives and design of the study and the availability of time, money and personnel Collection of Data
  18. 18.  To obtain information  To keep on record  To make decisions about important issues  To pass information onto others  For research study Purpose of Data Collection
  19. 19. Data collection is an extremely important part of any research because the conclusions of a study are based on what the data reveal How Important it is?
  20. 20. Nature, scope & objective of the enquiry Sources of information Availability of fund Techniques of data collection Availability of trained persons Factors to be considered before data collection
  21. 21. Example: Documents Creative works Interviews Man-made materials Surveys Example: Unpublished thesis and dissertations Manuscript Books Journals Sources of Data Source of Data External Primary Data Secondary Data Internal
  22. 22. Internal sources of Data o Many institutions and departments have information about their regular functions , for their own internal purposes o When those information are used in any survey is called internal sources of data o Eg. social welfare society External sources of data o When information is collected from outside agencies is called external sources of data o Such types of data are either primary or secondary o This type of information can be collected by census or sampling method by conducting survey Internal & External Sources of Data
  23. 23.  Data collected by investigator from personal experimental studies for a specific research goal is called primary data  The data are collected specially for a research project  Used when secondary data are unavailable and inappropriate  Data are to be unique, original, reliable and accurate in nature  Primary data hahe not been changed or altered by human beings, therefore its validity is greater than secondary data Primary Data
  24. 24. Demerits Evaluated cost Time consuming More number of resources are required Inaccurate feedback Required lot of skill with labor Targeted issues are addressed Data interpretation is better Merits High accuracy of data Greater control Address as specific research issues Primary Data
  25. 25. Interview (direct/indirect) Schedule Questionnaires survey Focus group discussion (FGD) Community forums and public hearings Observation Case studies Key informants interview Internet/E-mail/SMS Primary Data Collection Techniques
  26. 26.  The data is collected by the investigator personally, he/she must be a keen observer  He/she asks or cross-examines the informant and collects necessary information  It is original in character Direct personal observation
  27. 27. Direct personal observation is adopted in the following cases Where greater accuracy is needed Where the field of enquiry is not large Where confidential data are to be collected Where sufficient time is available Suitability of direct personal observation
  28. 28. Merits Original data True and reliable data Encouraging response because of personal approach A high degree of accuracy Direct personal observation Demerits Unsuitable in large area Expensive & time-consuming Untrained investigator brings worst results Collection of information according to the ease of the informant
  29. 29.  The investigator approaches the witness or third parties, who are in touch with the informant  The enumerator interviews the people, who are directly or indirectly connected with the problem under the study  Generally this method is employed by different enquiry committees and commissions  The police department generally adopts this method to get clues of thefts, riots , murders, etc. Indirect oral interview
  30. 30.  It is more suitable when the area to be studied is large  It is used when direct information cannot be obtained  This system is generally adopted by governments Suitability of indirect oral interview
  31. 31. Merits  Simple and convenient  Saves time, money and labor  Useful in investigation of a large area  Adequate information can be had Demerits  Information can’t be relied as absence of direct contact  Interview with an improper man will spoil the results  To get real data, a sufficient no. of people are to be interviewed  Careless attitude of informant affects the degree of accuracy Indirect oral interview
  32. 32.  The local agents or correspondents will be appointed, they collect the information and transmit it to the office or person  They do according to their own ways and tastes  Adopted by newspapers, agencies, etc.  The informants are generally called correspondents  Suitable in those cases where the information is to be obtained at regular intervals from a wide area Information through agencies
  33. 33. Merits Demerits  Extensive information can be had  It is the most cheap and economical method  Speedy information is possible  It is useful where information is needed regularly  The information may be biased  Degree of accuracy cannot be maintained  Uniformity cannot be maintained  Data may not be original Information through agencies
  34. 34.  The questionnaires is sent to the respondents, there are blank spaces for answers  A covering letter is also sent along with the questionnaire, requesting the respondent to extend their full cooperation  Adopted by research workers, private individuals, non-officials agencies and government  Appropriate in cases where informants are spread over a wide area Mailed questionnaires
  35. 35. Merits  Of all the methods, the mailed questionnaire is the most economical  It can be widely used, when the area of investigation is large  It saves money, labor and time Demerits  Cannot be sure about the accuracy and reliability of the data  There is long delay in receiving questionnaires duly filled in Mailed questionnaires
  36. 36.  Very similar to the questionnaire method  The main difference is that a schedule is filled by the enumerator who is specially appointed for the purpose  Enumerator goes to the respondents, asks them the questions from the Performa in the order listed, and records the responses in the space provided  Enumerators must be trained in administering the schedule Data Collection Through Schedules
  37. 37.  A detailed study of geographical area to gather data, attitudes, impressions, opinions, satisfaction level etc., by polling a section of the population Census Survey • Conducted regularly at large interval of time Continuous Survey • Conducted regularly and frequently Ad-hoc Survey • Conducted at specific times for specific need • ‘as and when’ required Survey Types
  38. 38. Merits Cover large population Less expensive Information is accurate Demerits On small scale survey avoided Time consuming Information does not penetrate deeply Researcher must have good knowledge Survey
  39. 39.  It is the method of comprehensive study of social unit which may be a person, a family, an institution, an organization or a community Merits Direct behavioral study Real & personal experience record Make possible the study of social change Increase analysis ability & skills Demerits One case almost different from another case Personal bias Use only in limit sphere More time & money consuming Case Study
  40. 40.  Useful to further explore a topic, providing a broader understanding of why the target group may behave or think in a particular way  And assist in determining the reason for attitudes and beliefs  Conducted with a small sample of the target group and  Used to stimulate discussion and gain greater insights Focus Group Discussion
  41. 41. Merits  Useful when exploring cultural values and health beliefs  Can be used to explore complex issues  Can be used to develop hypothesis for further research  Do not require participants to be literate Demerits  Lack of privacy/anonymity  Potential for the risk of ‘group think’  Potential for group to be dominated by one or two people  Group leader needs to be skilled at conducting focus groups, dealing with conflict, drawing out passive participants  Time consuming to conduct and analyse Focus Group Discussion
  42. 42.  Application and combination of several research methods in the study of the same phenomenon  Researchers can hope to overcome the weakness or intrinsic biases and the problems that come from single method, single-observer and single-theory studies  The purpose of triangulation in qualitative research is to increase the credibility and validity of the results Triangulation Types (Denzin 1978) Data Triangulation Investigator Triangulation Theory Triangulation Methodological Triangulation Beating the Bias
  43. 43.  Secondary data are those data which have been already collected and analysed by some earlier agency for its own use and later the same data are used by a different agency Published Sources Unpublished Sources Sources of Secondary Data Secondary Data
  44. 44. Various governmental, international and local agencies publish statistical data, and chief among them are:  International publications: They are UNO, WHO, Nature, etc.  Official publications of Government: Department of Drug Administration, Central Bureau of Statistics  Semi-Official publications: Semi-Govt. institutions like Municipal Corporation, District Board, etc. publish reports Published Sources
  45. 45.  Publications of Research Institutions: Nepal Development Research Institute, Nepalese Journal of Ophthalmology etc. publish the finding of their research program  Journals and Newspapers: Current and important materials on statistics and socio-economic problems can be obtained from journals and newspapers like, Swasthya Khabar Patrika, Health Today Magazine, The Sight, etc. Published Sources
  46. 46.  Records maintained by various government and private offices  Researches carried out by individual research scholars in the universities or research institutes According to Prof. Bowley “It is never safe to take published statistics at their face value without knowing their meaning and limitations and it is always necessary to criticize arguments that can be based on them.” Unpublished Sources
  47. 47. Before using the secondary data, the investigators should consider the following factors: Precautions in the use of Secondary Data Suitability of data Adequacy of data Reliability of data
  48. 48. Reliability of data – may be tested by checking: Who collected the data? What were the sources of the data? Was the data collected properly? Suitability of data Data that are suitable for one enquiry may not be necessarily suitable in another enquiry Objective, scope and nature of the original enquiry must be studied Adequacy of data – data is considered inadequate, if they are related to area which may be either narrower or wider than the area of the present enquiry Secondary Data must possess the following characteristics
  49. 49. Primary data o Real time data o Sure about sources of data o Help to give results/ finding o Costly and time consuming process o Avoid biasness of response data o More flexible Secondary data o Past data o Not sure about of sources of data o Refining the problem o Cheap and no time consuming process o Can not know in data biasness or not o Less flexible
  50. 50.  The characteristics or traits for which numerical value can not be assigned, are called qualitative data (attributes) e.g. gender, color, honesty etc.  Methods of collecting qualitative data Methods of Qualitative Data Collection Direct Observation In-depth Interview Case Study Triangulation Use of Secondary Data Assessment of Qualitative Data
  51. 51.  Classification of Qualitative data Qualitative Data Geographical Classification Chronological Classification Qualitative Classification Assessment of Qualitative Data
  52. 52. Tabulation of Qualitative Data  Qualitative data values can be organized by a frequency distribution  A frequency distribution lists – Each of the categories – The frequency/counts for each category Assessment of Qualitative Data
  53. 53. Frequency Table  A simple data set is: cataract, cataract, keratoconus, glaucoma, glaucoma, cataract, glaucoma, cataract  A frequency table for this qualitative data is  The most commonly occurring eye condition is cataract Eye condition Frequency Cataract 4 Keratoconus 1 Glaucoma 3 Assessment of Qualitative Data
  54. 54. What Is A Relative Frequency?  The relative frequencies are the proportions (or percents) of the observations out of the total  A relative frequency distribution lists – Each of the categories – The relative frequency for each category  Relative frequency = Frequency/Total Assessment of Qualitative Data
  55. 55. Relative Frequency Table  A relative frequency table for this qualitative data is  A relative frequency table can also be constructed with percents (50%, 12.5% and 37.5% for the above table) Refractive Error Relative Frequency Cataract .500 (=4/8) Keratoconus .125 (=1/8) Glaucoma .375 (=3/8) Assessment of Qualitative Data
  56. 56.  Graphical representation Of Qualitative Data Bar Diagram Pie or Sector Diagram Line Diagram Pictogram Map Diagram or Cartogram Assessment of Qualitative Data
  57. 57. Data Processing
  58. 58.  The data, after collection, has to be prepared for analysis  Collected data is raw and it must undergo some processing before analysis  The result of the analysis are affected a lot by the form of the data  So, proper data processing is must to get reliable result Data Processing
  59. 59.  Checking the questionnaires and schedules  Reduction of mass data to manageable proportion  Sum up the materials so as to prepare tables, charts, graphs and various groupings and breakdowns for presenting the result  Minimizing the errors which may creep in at various stage of the survey Objectives of Data Processing
  60. 60. 1. Manual Data Processing  Involves human intervention  Implies many chances for errors, such as delays in data capture, high amount of operator misprints  Implies higher labor expenses in regards to spending for equipment and supplies, rent, etc. Types of Data Processing
  61. 61. 2. Mechanical Data Processing  Different calculations and processing are performed using mechanical machines like calculators etc.  The use of mechanical machines makes data processing easier and less time- consuming  The chances of errors also become far less than manual data processing Types of Data Processing
  62. 62. 3. Electronic Data Processing  Processing of data by use of computer and its programs Types of Data Processing
  63. 63. 4. Real Time Processing  There is a continual input, process and output of data  Data has to be processed in a small stipulated time period (real time)  Eg, when a bank customer withdraws a sum of money from his or her account it is vital that the transaction be processed and the account balance updated as soon as possible Types of Data Processing
  64. 64. 5. Batch Processing  In a batch processing group of transactions collected over a period of time is collected, entered, processed and then the batch results are produced  Batch processing requires separate programs for input, process and output  It is an efficient way of processing high volume of data  Eg, Payroll system, examination system and billing system Types of Data Processing
  65. 65. QUESTIONNAIRE CHECKING EDITING CODING CLASSIFICATION TABULATION GRAPHICAL REPRESENTATION DATA CLEANINGDATA ADJUSTING The processing of data involves activities such as Important Steps in Data Processing
  66. 66.  When the data is collected through questionnaires, the first steps of data process is to check the questionnaires if they are accepted or not Not accepted if:  Gives the impression that respondent could not understand the questions  Incomplete partially or fully  Answered by a person who has inadequate knowledge Questionnaire Checking
  67. 67.  Process of examining the data collected in questionnaires/schedules to detect errors and omissions to correct these when possible to make sure the schedules are ready for tabulation Data Editing
  68. 68.  Editor is responsible for seeing that the data are; Accurate as possible Consistent with other facts secured Uniformly entered As complete as possible Acceptable for tabulation and arranged to facilitate coding tabulation Data Editing
  69. 69. • Data form complete • Free of bias, errors, inconsistency and dishonesty Editing for quality • Modification to facilitate tabulation, • Ignoring extremely high/low Editing for tabulation • Translating or rewriting Field editing • Wrong and replacement Central editing Types of Editing
  70. 70.  To gather information  To make data relevant and appropriate for analysis  To find errors and modify them  To ensures that the information provided is accurate  To establish the consistency of data  To determine whether or not the data are complete  To obtain the best possible data available Necessity of Editing
  71. 71.  Process of assigning numerals or other symbols to answers so that responses can be put into limited number of categories or classes  Translating answers into numerical values or assigning numbers to the various categories of a variable to be used in data analysis  Coding is done by using a code book, code sheet, and a computer card  Coding is done on the basis of the instructions given in the codebook  The codebook gives a numerical code for each variable Coding of Data
  72. 72. 72 • A codebook contains coding instructions and the necessary information about variables in the data set • A codebook generally contains the following information: - column number - record number - variable number - variable name - question number - instructions for coding Codebook
  73. 73.  To organize data code  To form structure for coding  For interpretation of data  For conclusions of data coded  To translating answers into numerical values  To assign no. to the various categories for data analysis  It is necessary for efficient analysis Necessity of Coding
  74. 74.  The process of arranging the primary data in a definite pattern and presenting it in a systematic way  The crude data obtained from experiment or survey is classified according to their properties  Classification cab be done by qualitatively or quantitatively Classification of Data
  75. 75.  The classified data is more easily understood  It presents the facts into a simpler form  It facilitates quick comparison  It helps for further statistical treatment such as average, dispersion etc.  It detects the error easily Objectives of classification
  76. 76. Qualitative classification Geographical classification Chronological classification Qualitative classification Quantitative classification Discrete classification Continuous classification Types of classification
  77. 77. Geographical Classification  Data are classified by location of occurrence (i.e. area, region) eg cataract pts. district wise Chronological classification  Data are classified by time of occurrence of the observations, events  The categories are arranged in chronological order eg, no. of trachoma pts. recorded from 2000 to 2010 Qualitative Classification
  78. 78. Qualitative classification (Classification according to attributes)  Data are classified according to some quality such as religion, literacy, sex, occupation etc. Simple classification  Classification is made into 2 classes, such as classification by male or female Manifold classification  2 or more than 2 attributes are studied simultaneously  Eg. Classification according to sex, again marital status and again literacy Qualitative Classification
  79. 79.  Process of systematic organization and recording of long series of data for further analysis and interpretation into rows and columns  It is concise, logical & orderly arrangement of data in a columns & rows Tabulation
  80. 80.  It presents an overall view of findings in a simpler way  To identify trends  It displays relationships in a comparable way between parts of the findings  It conserves space and reduces explanatory and descriptive statement to a minimum  It facilitates the process of comparison  It provides a basis for various statistical computations Usefulness of Tabulation
  81. 81. Graphical Representation  Graphs help to understand the data easily  A single picture is worth a thousand words-so goes a common saying  The non statistical minded people also easily understands the data and compares them  Most common graphs are bar charts and pie charts in qualitative study and histogram in quantitative study
  82. 82. Graphical Representation Advantages  It is easier to read  Can show relationship between 2 or more sets of observations in one look  Universally applicable  Has high communication power  Simplifies complex data  Has more lasting effect on brain
  83. 83. Presentation of Qualitative data 1. Bar Diagram • Consists of equally spaced vertical (or horizontal) rectangular bars of equal width placed on a common horizontal (or vertical) base line • The categories are placed on X-axis and their frequencies on Y-axis Graphical Representation
  84. 84. Graphical Representation 0 100 200 300 400 BPH MBBS B.Optom B.Pharma NO.OFSTUDENTS HEALTH PROGRAM Health Program at IOM Simple Bar diagram Component Bar diagram Multiple Bar diagram
  85. 85. Graphical Representation 2. Pie Chart • Circular diagram divided into segments and each segment represent frequency in a category
  86. 86. Graphical Representation Production of health manpower yearly Pictogram Line diagram Cartogram
  87. 87. Graphical Representation Presentation of Quantitative Data 1.Histogram • Graphical representation of a set of contiguously drawn bars • Most popular graph for continuous variable
  88. 88. Graphical Representation Frequency Polygon Frequency Curve Scatter Diagram Time Plot
  89. 89. Graphical Representation Stem-leaf Display Box-and-whisker Plot
  90. 90.  Includes consistency checks and treatment of missing responses  Although preliminary consistency checks have been made during editing, the checks at this stage are more thorough and extensive, because they are made by computer  Computer packages like SPSS, SAS, EXCEL and MINITAB can be programmed to identify out-of-range values for each variable Data Cleaning
  91. 91.  If any correction needs to be done for the statistical analysis, the data is adjusted accordingly Data Adjusting  Data adjusting is not always necessary but it may improve the quality of analysis sometimes Data Analysis
  92. 92. • Biostatistics by Prem P. Panta • Fundamentals of Research Methodology and Statistics by Yogesh k. Singh • Research Design by J. W. Creswell • Internet References Thank

×