This document discusses different methods for collecting data, both primary and secondary. It describes primary data collection methods like observation, surveys, interviews, questionnaires, and schedules. It provides details on how to conduct each method effectively and their advantages and disadvantages. Some key secondary data sources are also outlined such as internal organization records, external publications, reports and internet sources. When using secondary data, factors like reliability, suitability and adequacy must be considered. The selection of the appropriate data collection method depends on the nature, scope, budget and time constraints of the research.
A fantastic PPT on the topic collection of data. The PPT covers the concept of various sources of data and the relevant methods to collect primary and secondary data. It also states the various parameters to be considered while using secondary data.
Different Methods of Collection of DataP. Veeresha
Data collection is a term used to describe a process of preparing and collecting data.
Data are the basic inputs to any decision making process in any fields like education, business, industries…. etc
The primary data are those which are collected afresh and for the first time, and thus happen to be original in character. It is real time data and which are collected by the researcher himself.
Secondary data means data that are already available i.e., they refer to the data which have already been collected and analyzed by someone else.
The document outlines the 11 steps in the research process and applies them to understand Ishant's problem. It begins by defining the research problem as determining Ishant's specific issue, which is suspected to be dyslexia based on his symptoms. The objectives are then set as understanding dyslexia and how to help Ishant. Exploratory research is chosen as the design. Primary data will be collected through a questionnaire administered to Ishant's parents, brother, and teachers. The findings will then be analyzed and reported to understand Ishant's issue and how to address it.
Primary and Secondary Data collection - Ajay Anoj & GokulAJAY ANOJ KUMAR
The document discusses primary and secondary sources of data collection for research. It defines primary data as data collected directly by the researcher for the purposes of the research project. Secondary data is defined as data that was previously collected by others. The document outlines various methods for collecting both primary and secondary data, including surveys, interviews, observation, and reviewing published sources. It also compares primary and secondary data and discusses best practices for selecting an appropriate data collection method based on factors like the research objective, availability of funds, and required precision.
Here are some potential data collection methods for each topic:
a) Music tastes of class - survey (online or paper)
b) Average height of class - direct measurement
c) Parent housework time - survey (online or paper)
d) Malaysian student environmental attitudes - survey (online or paper)
The key is matching the appropriate quantitative or qualitative method to the data needed. Direct measurement works best for objective facts like height, while surveys can assess preferences, opinions and behaviors.
Data processing involves 5 key steps: editing data, coding data, classifying data, tabulating data, and creating data diagrams. It transforms raw collected data into a usable format through these steps of cleaning, organizing, and analyzing the data. First, data is collected from sources and prepared by cleaning errors. It is then inputted and processed using algorithms before being output and interpreted in readable formats. Finally, the processed data is stored for future use and reports.
This document discusses methods of collecting statistical data. It describes census and sample investigation methods. The census method collects data from every unit of the population, while the sample method collects data from only a few representative units. The census method is more reliable but costly, while the sample method is less expensive but less accurate. Key differences between the two methods are also outlined.
This document discusses different sampling methods used in research studies. It describes probability sampling methods like simple random sampling, systematic sampling, and stratified sampling which involve random selection. It also covers non-probability sampling techniques such as judgmental sampling, accidental sampling, quota sampling, and convenience sampling which do not use random selection. The key advantages of sampling over a census are lower cost, faster data collection, and feasibility when the entire population cannot be studied. However, sampling results in less accuracy than a census due to potential errors.
The document discusses various sampling techniques used in research including probability and non-probability sampling. It explains key concepts like population, sample, sampling frame, sampling error, systematic error. It describes different probability sampling designs such as simple random sampling, stratified sampling, cluster sampling and multistage sampling. It also discusses non-probability sampling techniques like convenience sampling and quota sampling. The document provides advantages and limitations of different sampling methods and guidelines for selecting an appropriate sampling design.
This document discusses various types of errors that can occur in sampling techniques, including sampling errors and non-sampling errors. It defines sampling errors as errors that arise from using a sample rather than the entire population. Non-sampling errors occur due to issues in data collection, processing, and analysis. Some key points made are that sampling error decreases with larger sample sizes, while non-sampling error does not necessarily decrease, and that important surveys conducted in Bangladesh include demographic, health, and nutrition surveys.
Data are distinct pieces of information collected for analysis to produce research results. There are two types of data: primary and secondary. Primary data is original data collected directly by the researcher through surveys, observation, or experimentation. Secondary data refers to data originally collected by someone else for another purpose that is now being used for a new study. Common methods for collecting primary data include observation, interviews, questionnaires, and schedules. Secondary data can come from government publications, journals, reports, and unpublished sources.
1) The document discusses various sampling methods used in medical research including simple random sampling, stratified sampling, and cluster sampling.
2) It explains the need for sampling over a complete census due to advantages like lower cost, ability to estimate errors, and feasibility for large populations.
3) Key concepts discussed include sampling units, frames, parameters, statistics, and different types of errors associated with sampling.
Primary data is collected directly by the researcher through methods like observation, interviews, questionnaires, and schedules. Observation can be structured, unstructured, participant, non-participant, controlled, or uncontrolled. Interviews can be personal, telephone-based, structured, unstructured, focused, clinical, or non-directive. Questionnaires are effective when respondents are educated and cooperative but have a low response rate. Schedules require enumerators to ask respondents questions from a form and record their answers.
This document discusses various techniques for collecting data. There are two main types of data collection: primary data and secondary data. Primary data involves directly collecting original data through methods like personal investigation, questionnaires, experiments, census, and sampling. Secondary data involves obtaining existing data from published sources like statistical agencies or unpublished sources like government records and research studies. Some specific primary data collection methods discussed include direct and indirect personal investigation, using correspondents, questionnaires sent by post or enumerators, experiments, census, and sampling.
This document summarizes and analyzes three cases of ethical controversy in research studies: Stanley Milgram's obedience study, Laud Humphrey's tearoom study, and Philip Zimbardo's Stanford prison experiment. It discusses how each of these studies violated ethical principles like informed consent, risks of harm, privacy, and allowing subjects to withdraw. The document also outlines guidelines for addressing ethical issues in research processes, sites, data collection, and ensuring respect, beneficence and justice for participants.
This document discusses various experimental research designs, including pre-experimental, true experimental, and randomized controlled trial designs. It provides examples and descriptions of different types of designs, such as one-shot case design, one-group pretest-posttest design, post-test-only control design, pretest-post-test-only design, Solomon four-group design, factorial design, randomized block design, and crossover design. The goal is to help students understand how to properly structure experiments to minimize threats to validity and draw accurate conclusions about causal relationships between independent and dependent variables.
Data collection is the process of systematically gathering and measuring information to answer questions and evaluate outcomes. There are three main sources of data: secondary data collected by others, internal data from within an organization, and primary data collected through questioning and observation. Questionnaires can be structured, with predetermined questions and responses, or unstructured, allowing respondents to answer freely in their own words. Properly designing questionnaires requires skill, as researchers must determine what information is needed, the questionnaire type and format, question content and response format, sequencing, and whether it will be disguised or structured. Factors like cover letters, question number, logical arrangement, simplicity, sensitivity, instructions, footnotes, objectivity, calculations, pre-testing, cross-
Data Collection tools: Questionnaire vs ScheduleAmit Uraon
Questionnaires and schedules are commonly used methods for collecting primary data. Questionnaires involve sending a standardized set of questions to respondents to answer on their own and return. Schedules are similar but involve an enumerator personally collecting responses by asking questions directly and filling out the schedule. Both methods can be used for descriptive or explanatory research and involve designing valid and reliable questions, representative sampling, and defining relationships between variables. Questionnaires are cheaper but have higher non-response rates while schedules provide more complete information through personal contact but are more expensive due to field workers.
This document discusses various methods for collecting data, both primary and secondary. It defines data as units of information that are measured, collected, analyzed and used for data visualizations. There are two main types of data collection methods discussed:
Primary methods involve directly collecting original data and include observation, surveys, interviews and questionnaires. Observation allows collecting large quantities of data in an inexpensive way but requires extensive training. Surveys can be conducted in-person or online and collect standardized information from a sample. Interviews are conducted one-on-one and allow collecting more in-depth information.
Secondary methods involve using existing data collected by others. Common secondary sources include publications, reports, and data available online. While cheaper and faster
methods of data collection research methodology.pptxYashwanth Rm
The document discusses various methods for collecting primary data in research, including observation, interviews, questionnaires, and schedules. It provides details on how to conduct each method effectively and compares their advantages and disadvantages. The key methods covered are observation, which collects data through direct observation in the field; interviews, which involve oral questioning; questionnaires, which are printed forms sent to respondents; and schedules, which are similar to questionnaires but involve an enumerator administering the questions.
Some common data collection methods include surveys, interviews, observations, focus groups, experiments, and secondary data analysis. The data collected ...
methods of data collection research methodology.pdfYashwanth Rm
The document discusses various methods for collecting primary data in research, including observation, interviews, questionnaires, and schedules. It provides details on how to conduct each method effectively and compares their advantages and disadvantages. The key methods covered are observation, where a researcher directly watches subjects; interviews, conducted in-person or over the phone; questionnaires, which are distributed to respondents; and schedules, which involve an enumerator asking respondents questions from a structured form.
Methods of data collection (research methodology)Muhammed Konari
This document discusses different methods for collecting primary data, including observation, interviews, questionnaires, and schedules. It provides details on each method:
Observation methods involve systematically observing participants and recording data. Interviews can be structured or unstructured, and involve an interviewer asking respondents questions. Questionnaires are printed forms sent to respondents to complete on their own, while schedules are similar forms that an enumerator completes by interviewing respondents. Each method has advantages like producing large datasets, but also disadvantages such as being time-consuming or open to bias.
Methods of data collection (research methodology)Muhammed Konari
Included all types of data collection.Includes primary data collection and secondary data collection. Described each and every classification of Data collections which are included in KTU Kerala.
This document discusses different methods for collecting primary data, including observation, interviews, questionnaires, and schedules. It provides details on each method such as the steps involved, types or classifications, advantages, and disadvantages. The key methods covered are observation, where a researcher directly observes participants; interviews, which involve asking participants questions; questionnaires, which are forms mailed to participants to complete; and schedules, where an enumerator asks participants questions and records responses, similar to interviews.
This document discusses various methods for collecting data for research purposes. It describes primary data collection methods like observation, interviews, questionnaires, and surveys which involve directly collecting original data. Secondary data collection involves using existing data collected by others. The key primary data collection methods covered are observation, interviews, questionnaires, and their types and steps. The advantages and disadvantages of each method are also outlined.
The document discusses various methods for collecting data in research. It describes primary and secondary data collection. Some key methods covered include observation, interviews, questionnaires, schedules, and surveys. For each method, it provides details on the process, types, advantages, and disadvantages. The goal of the document is to outline different approaches for gathering information needed to conduct research.
This document discusses various methods for collecting data, including primary and secondary data collection. It describes primary data collection methods such as experiments, surveys, observation, and interviews. Specifically, it outlines structured and unstructured observation, as well as participant and non-participant observation. It also discusses personal interviews, questionnaires/schedules, and their advantages and disadvantages. Secondary data collection involves using existing data from government publications, organizations, and other sources. When using secondary data, the researcher must evaluate its reliability, suitability, and adequacy for the research purpose.
This document discusses various methods for collecting primary data, including observation, interviews, questionnaires, and schedules. It provides details on how to conduct structured and unstructured observation, as well as disguised, undisguised, controlled, and uncontrolled observation. For interviews, it outlines personal and telephone interviews, and structured, semi-structured, and unstructured interview types. It also discusses how to construct questionnaires and the advantages and disadvantages of questionnaires and schedules. Secondary data collection and steps for data analysis like editing, coding, data entry, validation, and tabulation are also covered.
The document discusses different methods of collecting primary and secondary data. It describes primary data collection methods such as observation, interviews using questionnaires/schedules, and surveys. It provides details on structured vs unstructured observation, participant vs non-participant observation, and structured vs unstructured interviews. It also discusses advantages and limitations of interviews and questionnaires. Secondary data collection involves obtaining published data from various sources such as government publications, books, reports, and public records. When using secondary data, the researcher must evaluate the reliability, suitability, and adequacy of the data.
This document discusses various methods of data collection that researchers use in studies, including observation, interviews, questionnaires, and archival data. It provides details on the different types of observation (controlled, participant), interviews (structured, semi-structured, unstructured), and considerations for each method. The document also outlines questionnaires as a method and considerations like response rates. Overall, the document serves as an overview of common data collection methods, their uses, and factors to consider like reliability, validity, and biases.
This document discusses various methods for collecting data, including definitions, types, categories, and sources of data. It describes primary and secondary data and how each are collected. Common data collection methods like questionnaires, interviews, observation, and document analysis are explained along with their advantages and disadvantages. The key points are that there are various ways to collect both quantitative and qualitative data, and the optimal method depends on factors like the research question and available resources. Primary sources involve collecting original data while secondary sources use previously collected data.
This document discusses various methods for collecting primary and secondary data. It describes primary data collection methods like observation, interviews (structured and unstructured), questionnaires, and surveys. It also discusses secondary data sources and factors to consider when using secondary data like reliability, suitability, and adequacy. The key methods covered include observation, personal interviews, telephone interviews, questionnaires, and surveys. It provides details on the advantages and disadvantages of each method.
This document discusses various methods for collecting primary and secondary data. It describes primary data collection methods such as observation, interviews, questionnaires, and schedules. It provides details on structured vs unstructured observation, participant vs non-participant observation, and types of interviews. It also discusses constructing questionnaires and using secondary data sources.
This document discusses different methods for collecting data in scientific research, focusing on questionnaires and interviews. It provides details on how to design and administer questionnaires, including defining objectives, writing questions, and pilot testing. It also describes structured, semi-structured, and in-depth interviews. Focus group discussions are explained as a way to stimulate conversation around a topic and cross-check opinions. Questionnaires allow collecting large amounts of subjective and objective data but depend on honesty, while interviews provide more context and understanding but are more time intensive.
This document discusses various data collection methods and tools used in nursing research. It describes primary and secondary data collection methods. Primary methods involve directly collecting data from subjects through surveys, interviews, observations or physiological measurements. Secondary methods use existing data collected for other purposes. Some advantages of primary methods are they can be tailored to research needs and ensure completeness of data, while disadvantages include being time-consuming. Common data collection tools discussed include questionnaires, interviews and physiological measurements. Different types of interviews like unstructured, semi-structured and structured are also described.
The document discusses research design and methods of data collection. It defines research design as a plan to answer research questions and identifies common types like historical, descriptive, case study, experimental, and ethnographic designs. It also discusses sampling methods, both probability and non-probability. Primary and secondary data collection methods are covered, including observation, interviews, questionnaires, and surveys. Guidelines for developing questionnaires and conducting surveys are provided.
This document discusses various methods and techniques for collecting data. It begins by defining data collection as the process of gathering quantitative and qualitative information on variables to evaluate outcomes. Some key methods covered include interviews, questionnaires, observation, and record analysis. The document provides details on each method, including their purposes, advantages, disadvantages, and specific tools or techniques used. It emphasizes that the appropriate data collection method depends on factors like the study topic, sample size, and available resources.
Cómo hemos implementado semántica de "Exactly Once" en nuestra base de datos ...javier ramirez
Los sistemas distribuidos son difíciles. Los sistemas distribuidos de alto rendimiento, más. Latencias de red, mensajes sin confirmación de recibo, reinicios de servidores, fallos de hardware, bugs en el software, releases problemáticas, timeouts... hay un montón de motivos por los que es muy difícil saber si un mensaje que has enviado se ha recibido y procesado correctamente en destino. Así que para asegurar mandas el mensaje otra vez.. y otra... y cruzas los dedos para que el sistema del otro lado tenga tolerancia a los duplicados.
QuestDB es una base de datos open source diseñada para alto rendimiento. Nos queríamos asegurar de poder ofrecer garantías de "exactly once", deduplicando mensajes en tiempo de ingestión. En esta charla, te cuento cómo diseñamos e implementamos la palabra clave DEDUP en QuestDB, permitiendo deduplicar y además permitiendo Upserts en datos en tiempo real, añadiendo solo un 8% de tiempo de proceso, incluso en flujos con millones de inserciones por segundo.
Además, explicaré nuestra arquitectura de log de escrituras (WAL) paralelo y multithread. Por supuesto, todo esto te lo cuento con demos, para que veas cómo funciona en la práctica.
LLM powered contract compliance application which uses Advanced RAG method Self-RAG and Knowledge Graph together for the first time.
It provides highest accuracy for contract compliance recorded so far for Oil and Gas Industry.
Amazon Aurora 클러스터를 초당 수백만 건의 쓰기 트랜잭션으로 확장하고 페타바이트 규모의 데이터를 관리할 수 있으며, 사용자 지정 애플리케이션 로직을 생성하거나 여러 데이터베이스를 관리할 필요 없이 Aurora에서 관계형 데이터베이스 워크로드를 단일 Aurora 라이터 인스턴스의 한도 이상으로 확장할 수 있는 Amazon Aurora Limitless Database를 소개합니다.
[D2T2S04] SageMaker를 활용한 Generative AI Foundation Model Training and TuningDonghwan Lee
이 세션에서는 SageMaker Training Jobs / SageMaker Jumpstart를 사용하여 Foundation Model 을 Pre-Triaining 하거나 Fine Tuing 하는 방안을 제시합니다. 이 세션을 통해 아래 3가지가 소개됩니다.
1. 파운데이션 모델을 처음부터 Training
2. 오픈 소스 모델을 사용하여 파운데이션 모델을 Pre-Training
3. 도메인에 맞게 모델을 Fine Tuning하는 방안
발표자:
Miron Perel, Principal ML GTM Specialist, AWS
Kristine Pearce, Principal ML BD, AWS
How We Added Replication to QuestDB - JonTheBeachjavier ramirez
Building a database that can beat industry benchmarks is hard work, and we had to use every trick in the book to keep as close to the hardware as possible. In doing so, we initially decided QuestDB would scale only vertically, on a single instance.
A few years later, data replication —for horizontally scaling reads and for high availability— became one of the most demanded features, especially for enterprise and cloud environments. So, we rolled up our sleeves and made it happen.
Today, QuestDB supports an unbounded number of geographically distributed read-replicas without slowing down reads on the primary node, which can ingest data at over 4 million rows per second.
In this talk, I will tell you about the technical decisions we made, and their trade offs. You'll learn how we had to revamp the whole ingestion layer, and how we actually made the primary faster than before when we added multi-threaded Write Ahead Logs to deal with data replication. I'll also discuss how we are leveraging object storage as a central part of the process. And of course, I'll show you a live demo of high-performance multi-region replication in action.
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❻❸❼⓿❽❻❷⓿⓿❼ SATTA MATKA DPBOSS KALYAN MATKA RESULTS KALYAN CHART KALYAN MATKA ...
ppt mgt.pptx
1. What is DATA?????
Data are simply units of information.
Data are measured, collected, reported, analyzed, and
used to create data visualizations such as graphs, tables
or Images.
Data are the set of values of qualitative or
quantitative variables about one or more persons
or objects.
3. Qualitative Data (categorial)
Qualitative data is the data that can be arranged into
categories based on physical traits, gender, colors or
anything that does not have a number associated with it.
Qualitative-involves more details tells you why, when and
how!
Examples-
4. What is Data Collection?
It is the process by which the
researcher collects the information
needed to answer the research
problem.
The task of data collection begins
after a research problem has been
defined.
5. In collecting the data,the researcher must decide:
Which data is to collect?
How to collect the Data?
Who will collect the Data?
When to collect the Data?
7. Methods of Data Collection
Essentialy Two Types:
PRIMARY DATA
Primary data are those which are collected for
the first time and are original in character.
SECONDARY DATA
Secondary data are those which have already
been collected-by someone else.
9. Methods of Collecting Primary Data
• Observation
• Surveys
• Interviews
• Questionnaires
• Schedules
Primary
Data may
be
collected
through:
10. 1. Observation Method
Observation method is a method under which data
from the field is collected with the help of
observation by the observer or by personally going to
the field.
11. Steps ForAn Effective Observation
Determine what needs to be observed
Select participants
Random/Selected
Conduct the observation
(venue, duration, recording materials, take photographs )
Compile data collected
Analyze and interpret data collected
12. Types of OBSERVATION Methods
1- Structured Observation
When the observation is characterized by a careful definition
of the units to be observed (predefined), the style of recording the
observed information, standardized conditions of observation and
the selection of related data of observation.
2- Unstructured Observation
When it takes place without the above characteristics.
(Not predefined)
13. 3- Participant Observation
When the observer is member of the group which he is
observing then it is Participant Observation.
4- Non-Participant Observation
When the observer is not the member of the group
which he is observing then it is Non-Participant Observation.
• observer is observing people without giving any
information to them.
14. 5- Uncontrolled Observation
When the observation takes place in natural contition i.e.,
uncontrolled observation.It is done to get spontaneous picture of
life and persons.
6- Controlled Observation
When observation takes place according to pre-arranged
plans, with experimental procedure then it is controlled observation
generally done in laboratory under controlled condition.
15. Advantages of observation Method
Produces Large quantities of data.
All data obtained from observations are usable.
The observation technique can be stopped or begun at any time.
Relative Inexpensive
16. disadvantages of observation Method
Interviewing selected subjects may provide more
information, economically, than waiting for the
spontaneous occurrence of the situation.
Limited information
Extensive Training is needed.
17. ONE OF THE WIDELY USED RESEARCH
DESIGN TO COLLECT DATA IS
SURVEYS
18. How to collect Primary information through survey
A researcher can collect information
either
by observation
or
by asking.
WHEN HE/SHE ASKS FOR INFORMATION, WE SAY
THAT HE/SHE IS CONDUCTING A SURVEY.
19. 2. SURVEY Method
A ‘survey’ is a technique of gathering information
by questioning those individuals who are the
object of the research belong to a representative
sample, through standardized or questioning
procedure, with the aim of studying the
relationship among the variables and/or collecting
information that probably describe the whole
population.
20. There may be different ways to conduct
surveys…
In-Home Computer-Assisted
Personal Interviewing
E-mail Internet
Survey
Methods
Telephonic
Survey
Personal Electronic
21. 3.Interview Method
The Interview Method of collecting data
involves presentation of oral-verbal stimuli
and reply in terms of oral- verbal responses.
where the questions are asked personally
directly to the respondent.
Interviewer asks questions to respondent.
(which are aimed to get information
required for study)
22. Prepare interview schedule
Select subjects/ key Respondent
Conduct the interview
Analyze and interpret data collected from the interview
Steps ForAn EffectiveInterview
23. Types of Interview Methods
1- Structured Interviews :
In this case, a set of predecided questions
are there.
2- Unstructured Interviews :
In this case, we don’t follow a system of
pre-determined questions.
24. 3- Focused Group Interview
Unstructured and Free flowing
Focus Group has one Moderator
Moderator maintains control and focuses discussion
It involves 6 to 10 people
Group interview start with broad topic and focus in on
specific issues
Relatively homogeneous
Similar lifestyles and experiences
Generate discussion and interaction
Listens to what people have to say
Everyone gets a chance to speak
25. 4- Clinical Interviews :
• Information is generated and utilized at every step this process
including the activities of investigation, observation,
monitoring, diagnosis, planning, treatment and review.
• They also record their plans, orders, procedures performed,
observations, test results, opinions and discussions.
5- Group Interviews :
It is done in a group of 6 to 8 individuals is interviewed.
26. 6- Qualitative and quantitative Interviews :
It is divided on the basis of subject matter i.e.,
whether qualitative or quantitative.
7- Individual Interviews :
Interviewer meets a single person and
interviews him.
8- Selection Interviews :
Done for selection of people for certain Jobs.
27. Advantages of Interview Method
More information at greater
depth can be obtained
Resistance may be overcome by
a skilled interviewer
Personal information can be
obtained
28. disadvantages of Interview Method
It is an expensive Method
Interviewer bias
Respondent bias
Time consuming
29. 4.Questionnaires
The term “questionnaire” refers to an instrument for
the collection of data, usually in written form,
consisting of open/closed questions and other
enquiries requiring a response from subjects.
A Questionnaire is sent ( by post or by mail ) to the
persons concerned with a request to answer the
questions and return the Questionnaire.
A Questionnaire consists of a number of questions
printed in a definite order on a form.
30. Steps ForAn Effective Questionnaire
Prepare questions
(Formulate & choose types of questions, order them, write instructions, make copies)
Select your respondents
Random/Selected
Administer the questionnaire
(date, venue, time )
Tabulate data collected
Analyze and interpret data collected
31. Types of Questionnaire Methods
1- Open-ended questions
This gives the respondents the ability to respond in their own
words.
2- Close-ended or fixed alternative questions
This allows the respondents to choose one of the given
alternatives.
Types:- Dichotomous questions and Multiple Questions.
32. Essentials of Good Questionnaire
Should be short and simple
Follow a sequence of questions from easy to difficult one
Technical terms should be avoided
Should provide adequate space for answers in
questionnaire
Directions regarding filling of questionnaire should be
given Physical Appearance – Quality of paper, Color
Sequence must be clear
33. advantages of questionnaire Method
Low cost –even when the universe is large and is widespread
Free from interviewer bias
Responddents have adequate time to think through the answers.
Respondents who are not easily approachable, can also be reached
conveniently.
Large samples can be used
34. disadvantages of questionnaire Method
Time consuming
The respondents need to be educated and cooperative
This method is slow
Possibility of unclear replies.
35. 5.Schedules
Very similar to 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
Questionnaire in the order listed, and
records the responses in the space
provided.
Enumerator must be trained in
administering the schedule.
36. Questionnaire Vs. Schedule
Questionnaire
Q generally send to through mail
and no further assistance from
sender.
Q is cheaper method.
Non response is high.
In questionnaire, it is not confirmed
that expected respondent have
filled the answers.
Schedule
Schedule is filled by
the enumerator or
research worker.
Costly requires field
workers.
Non response is low.
In schedule identity of
person is known.
37. Questionnaire
Very slow method.
Incomplete and wrong
Information is more.
No personal contacts.
Depends on the quality
of questionnaire.
Q can used only when
respondent is educated
and well cooperative.
Schedule
Information is collected well
on time.
Depends on Honesty of the
enumerator.
Direct personal contacts.
Relatively more correct and
complete.
Information can be collected
from illiterates also.
Questionnaire Vs. Schedule
38. Secondary Data Collection Methods
• Data gathered and recorded by someone else.
• Secondary data is data that has been collected for
another purpose.
• It involves less cost, time and effort.
• Secondary data is data that is being reused. Usually
in a different context.
• For example: data from a book.
39. SOURCES of secondary data collection
INTERNAL SOURCES
Internal sources of secondary data are usually for
marketing application-
Sales Records
Marketing Activity
Cost Information
Distributor reports and feedback
Customer feedback
41. Other Sources of secondary data collection:
• Publications of Central, state , local government
• Technical and trade journals
• Books, Magazines, Newspaper
• Reports & publications of industry ,bank, stock
exchange
• Reports by research scholars, Universities,
economist
• Public Records
Secondary DataSources
42. • Reliability of data - Who, when , which methods, at what time
etc. must be investigated.
• Suitability of data – Object ,scope, and nature of original inquiry
should be studied, as if the study was with different objective
then that data is not suitable for current study
• Adequacy of data– Level of accuracy, • Area differences then
data is not adequate for study
Factors to be consideredbefore using secondary data
43. Nature ,Scope and object of inquiry
Availability of Funds
Time Factor
Accuracy Required
Selection of proper Methodfor collection of Data