This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then distinguishes between probability sampling methods, like simple random sampling, systematic sampling, and stratified sampling, which assign a known probability of selection to units, and non-probability sampling methods, which do not. The document provides details on how to implement different probability sampling techniques and discusses their relative advantages and disadvantages. It emphasizes that the goal of sampling is to select a subset of a population that is representative of the whole.
This study examined the effects of different warm-up conditions on explosive force production and jumping performance. Sixteen participants performed warm-ups consisting of no warm-up (control), running, static stretching, running plus stretching, and running plus stretching plus practice jumps. Two jumping tests were then performed to assess force production and jumping ability. The results showed that the static stretching warm-up produced the lowest force and jumping scores, while the running and running plus practice jumps warm-ups produced the highest scores. There were no differences between the control and running plus stretching warm-ups, but running alone produced better scores than running plus stretching. This suggests that running and practice jumps have a positive effect on explosive force and jumping, while static stretching
The document summarizes key concepts from Chapter Two of the 10th Edition of the psychology textbook "Psychology: An Introduction" by Benjamin Lahey. It discusses the scientific method, empirical evidence, theories, hypotheses, research methods such as descriptive studies, experiments, and statistics. It also covers ethical principles of research involving human and animal participants, including informed consent, confidentiality, and equal representation.
This document provides an overview of research methodology. It discusses what research is, the objectives and characteristics of research, and the scientific method. It also describes the different types of research, the research process, and the role of research in decision making. The key points covered include:
- Research is a systematic process of investigating a problem to discover answers through empirical evidence and careful analysis.
- The objectives of research are to gain new insights, describe characteristics, determine frequencies of occurrences, and test hypotheses.
- Research follows the scientific method and aims to systematically relate facts through observation, experimentation, and logical arguments.
- The research process involves defining the problem, reviewing literature, formulating hypotheses, designing the
This document provides an introduction to research methodology for midwifery students. It defines research and describes the different types. The research process is outlined including topic selection, which involves prioritizing problems based on criteria like feasibility and applicability. Quantitative and qualitative research approaches are also defined. Later sections discuss analyzing problems, formulating problem statements and stating problems clearly. The importance of a well-defined problem statement for developing the research proposal is emphasized.
This document discusses research methodology and defines research. It provides definitions from Merriam-Webster for research as a careful search or investigation aimed at discovering facts and revising theories. Research is described as an organized, systematic, and data-driven process of identifying a problem, gathering relevant information to analyze, and making conclusions to find answers or solutions. The document also discusses the purpose of research as creating new knowledge or adding to existing literature through basic and applied research approaches.
This document provides guidance for medical students on conducting health research. It outlines the key steps in the research process, including developing learning objectives and a research proposal. The proposal involves selecting a topic, reviewing existing literature, developing objectives and hypotheses, and detailing the methodology, work plan, and dissemination of results. The document also reviews best practices for writing a final research report, which consists of components like an abstract, introduction, methodology, results, discussion, and conclusions. The overall document serves to introduce medical students to the basics of the health research process.
This document provides guidance on writing the materials and methods section of a research study. It discusses including a list of all materials used, such as live organisms, reagents, chemicals, and experimental units. The materials and methods section should specify these materials in sufficient detail and describe the procedures to allow others to evaluate and replicate the study. It is important to control for experimental error by using proper research design, replication, and statistical analysis to reduce or eliminate errors from instruments, limited samples or trials, and lack of controls. The materials and methods section should be written in an expository style using future tense for proposed studies and past tense for technical reports, without personal pronouns, spelling out numbers if they start sentences, and including diagrams to
This study examined the effects of different warm-up conditions on explosive force production and jumping performance. Sixteen participants performed warm-ups consisting of no warm-up (control), running, static stretching, running plus stretching, and running plus stretching plus practice jumps. Two jumping tests were then performed to assess force production and jumping ability. The results showed that the static stretching warm-up produced the lowest force and jumping scores, while the running and running plus practice jumps warm-ups produced the highest scores. There were no differences between the control and running plus stretching warm-ups, but running alone produced better scores than running plus stretching. This suggests that running and practice jumps have a positive effect on explosive force and jumping, while static stretching
The document summarizes key concepts from Chapter Two of the 10th Edition of the psychology textbook "Psychology: An Introduction" by Benjamin Lahey. It discusses the scientific method, empirical evidence, theories, hypotheses, research methods such as descriptive studies, experiments, and statistics. It also covers ethical principles of research involving human and animal participants, including informed consent, confidentiality, and equal representation.
This document provides an overview of research methodology. It discusses what research is, the objectives and characteristics of research, and the scientific method. It also describes the different types of research, the research process, and the role of research in decision making. The key points covered include:
- Research is a systematic process of investigating a problem to discover answers through empirical evidence and careful analysis.
- The objectives of research are to gain new insights, describe characteristics, determine frequencies of occurrences, and test hypotheses.
- Research follows the scientific method and aims to systematically relate facts through observation, experimentation, and logical arguments.
- The research process involves defining the problem, reviewing literature, formulating hypotheses, designing the
This document provides an introduction to research methodology for midwifery students. It defines research and describes the different types. The research process is outlined including topic selection, which involves prioritizing problems based on criteria like feasibility and applicability. Quantitative and qualitative research approaches are also defined. Later sections discuss analyzing problems, formulating problem statements and stating problems clearly. The importance of a well-defined problem statement for developing the research proposal is emphasized.
This document discusses research methodology and defines research. It provides definitions from Merriam-Webster for research as a careful search or investigation aimed at discovering facts and revising theories. Research is described as an organized, systematic, and data-driven process of identifying a problem, gathering relevant information to analyze, and making conclusions to find answers or solutions. The document also discusses the purpose of research as creating new knowledge or adding to existing literature through basic and applied research approaches.
This document provides guidance for medical students on conducting health research. It outlines the key steps in the research process, including developing learning objectives and a research proposal. The proposal involves selecting a topic, reviewing existing literature, developing objectives and hypotheses, and detailing the methodology, work plan, and dissemination of results. The document also reviews best practices for writing a final research report, which consists of components like an abstract, introduction, methodology, results, discussion, and conclusions. The overall document serves to introduce medical students to the basics of the health research process.
This document provides guidance on writing the materials and methods section of a research study. It discusses including a list of all materials used, such as live organisms, reagents, chemicals, and experimental units. The materials and methods section should specify these materials in sufficient detail and describe the procedures to allow others to evaluate and replicate the study. It is important to control for experimental error by using proper research design, replication, and statistical analysis to reduce or eliminate errors from instruments, limited samples or trials, and lack of controls. The materials and methods section should be written in an expository style using future tense for proposed studies and past tense for technical reports, without personal pronouns, spelling out numbers if they start sentences, and including diagrams to
Research is the systematic and objective analysis and recording of controlled observations that may lead to the development of generalizations, principles, or theories, resulting in prediction and possible control of events .
1. Research design involves determining what, where, when, how, and by what means data will be collected and analyzed for a research study.
2. Key components of a research design include the sampling design, observational design, statistical design, and operational design. It must also specify the research problem, data collection and analysis methods, and population.
3. Research design can be exploratory, descriptive, or experimental. Exploratory research generates hypotheses, descriptive research observes characteristics, and experimental research tests hypotheses by manipulating variables.
The word ‘Research’ is comprised of two words Re + Search.
It means to search again. So research means a systematic investigation or activity to gain new knowledge of the already existing facts.
This document discusses research methodology and sampling techniques. It covers key topics such as census versus sample surveys, sampling design, steps in sampling design including defining the population, sampling unit, sample size, and sampling procedure. Factors that could lead to systematic bias are also outlined. The goal in selecting a sampling procedure is to minimize both systematic bias and sampling error while considering costs. Choosing an appropriate sampling technique is an important part of developing a reliable research methodology.
Research methodology, design, meaning, features, need, Sampling, errors in su...Prashant Ranjan
The document discusses research design and methodology. It defines research design and outlines its key features and needs. It describes different types of research designs including exploratory, descriptive, diagnostic, and hypothesis testing. It also discusses sampling, including probability and non-probability sampling. Finally, it covers potential errors in surveys such as sampling errors and non-sampling errors.
This document discusses quantitative research methods. It explains that quantitative research aims to quantify and measure social phenomena numerically in order to examine relationships between variables statistically. Some key points covered include:
- Quantitative research methods include surveys, experiments, and analyzing numerical data. Surveys can be administered in-person, by phone, mail, or online.
- Closed-ended questions are easier to analyze but may limit responses, while open-ended questions provide more flexibility but are harder to analyze.
- Various survey methods like in-person, phone, and mail have different strengths and weaknesses in terms of cost, response rates, and control. Experimental research assigns participants to groups to study causal relationships.
MEANING OF RESEARCH
OBJECTIVES OF RESEARCH
CHARACTERISTICS OF RESEARCH
CRITERIA OF A GOOD RESEARCH
QUALITIES OF GOOD RESEARCH
RESEARCH MOTIVATIONS
TYPES OF RESEARCH
PROBLEMS IN RESEARCH
RESEARCH APPROACHES
RESEARCH PROCESS
LITERATURE REVIEW
HYPOTHESIS
CRITERIA OF GOOD RESEARCH
PROBLEMS ENCOUNTERED BY RESEARCHER
Learn the process of Research.
Research process consists of a series of actions or steps necessary to carry out research. It guides a researcher to conduct research in a planned and organized sequence.
The document provides an overview of survey research and questionnaire design. It discusses that surveys are used to collect data and facts from a target population about a certain situation or issue. The key steps in survey research include developing hypotheses, designing the survey questions and format, sampling, data collection, analysis, and reporting findings. It also describes different types of surveys, methods of data collection including mail, interview and telephone surveys, and considerations for question structure, format, and response options. The document emphasizes that carefully designing and testing the questionnaire is important for effective survey research.
Samples are used in research studies to represent larger populations. While studying the entire population would provide the best data, samples are smaller and less expensive. Researchers define both the target population they wish to generalize to and the accessible population they can actually study. Random sampling involves chance to select participants while nonrandom sampling selects participants based on specific characteristics. Common sampling techniques include simple random, stratified, cluster, systematic, and convenience sampling.
Research Challenges - Characteristics of a Good Researcher Dr. Mazlan Abbas
This document discusses characteristics of good researchers and challenges in research. It provides definitions of basic and applied research, explaining that basic research expands knowledge while applied research solves practical problems. It also distinguishes between degrees (Bachelor's), Masters, and PhDs, illustrating how each level deepens knowledge in a specialty area. The document notes that choosing a good research problem takes time and is subjective. It also outlines common research approaches like mathematical modeling, simulation, and experimentation, and discusses managing researchers and their expectations around creativity and knowledge generation.
The document provides information on various sampling techniques used in research. It defines key terms like population, sample, sampling, and element. It describes different probability sampling techniques like simple random sampling, stratified random sampling, systematic random sampling, and cluster sampling. It also covers non-probability sampling techniques such as purposive sampling and convenience sampling. The document discusses the purposes, processes, merits, and limitations of different sampling methods.
Research is defined as a systematic effort to gain new knowledge. It involves formulating a research problem, conducting a literature review, developing hypotheses, designing a study, collecting and analyzing data, and reporting findings. The goal of research is to discover answers to questions through objective and systematic methods of finding solutions.
The document discusses the meaning, objectives, characteristics, types, and steps of research. It defines research as a systematic, directed search for knowledge. The main objectives of research are to gain new insights or accurately describe characteristics. Research is characterized by careful investigation and testing of conclusions. The main types discussed are descriptive, analytical, applied, fundamental, quantitative, and qualitative research. Key steps include formulating the problem, reviewing literature, developing hypotheses, collecting and analyzing data, and reporting findings. Research design involves determining what, why, where, when of a study. It is important for testing hypotheses and controlling for extraneous variables.
Foundations of Agricultural Research by Prof Jayne MugweJayne Mugwe
This PPT presentation gives overview of Agricultural Research. Explains meaning of scientifc research, Characteristics of research, research process at a glance, Importance of research and research development continnum
Prof Jayne Mugwe
Kenyatta University
This document provides information about research methodology. It begins by defining what research is, noting that research is a systematic process of finding answers to questions through a search for truth and new knowledge. The document then discusses what can be classified as research through some examples. It also covers the research process, which involves defining the problem, reviewing literature, formulating objectives and hypotheses, designing the methodology, collecting and analyzing data, and reporting findings. Additional topics covered include the purpose of reviewing literature, identifying a research problem, and recording literature through source cards and note cards.
The document outlines the scientific research method and provides guidance on developing mathematical models and completing a thesis. It describes the four main steps of the scientific method as observation, hypothesis, experimental testing, and predictions. Observation involves recognizing facts or occurrences, which are then used to form a hypothesis. The hypothesis is then tested experimentally, and if proven true, predictions can be made. Mathematical models, such as using equations to fit experimental data, can help test hypotheses and predictions. Following the scientific method and reporting iterations that include publishable results are keys to completing a successful thesis.
This document discusses different types of study designs used in medical research, including qualitative and quantitative methods. It covers observational studies like cohort and case-control studies, as well as experimental designs like randomized controlled trials. For each study type, it outlines their purpose, strengths, weaknesses and the types of research questions they can help answer. The goal is to help researchers choose the most appropriate design based on their specific research question and aims.
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then distinguishes between probability sampling methods, like simple random sampling, systematic sampling, and stratified sampling, and non-probability sampling methods. For each method, it provides details on how the sampling is conducted and notes advantages and disadvantages. The goal is to help readers understand different approaches to collecting representative samples from a population in a way that allows results to be generalized.
This document discusses different sampling methods used in research. It begins by defining sampling as selecting a subset of units from a larger population. The document then covers probability sampling methods like simple random sampling, systematic sampling, and stratified sampling. It also discusses non-probability sampling and provides examples. For each method, it describes how to implement the technique and highlights advantages and disadvantages. The key goal is to help readers understand how to appropriately select samples to gather data about a target population.
Research is the systematic and objective analysis and recording of controlled observations that may lead to the development of generalizations, principles, or theories, resulting in prediction and possible control of events .
1. Research design involves determining what, where, when, how, and by what means data will be collected and analyzed for a research study.
2. Key components of a research design include the sampling design, observational design, statistical design, and operational design. It must also specify the research problem, data collection and analysis methods, and population.
3. Research design can be exploratory, descriptive, or experimental. Exploratory research generates hypotheses, descriptive research observes characteristics, and experimental research tests hypotheses by manipulating variables.
The word ‘Research’ is comprised of two words Re + Search.
It means to search again. So research means a systematic investigation or activity to gain new knowledge of the already existing facts.
This document discusses research methodology and sampling techniques. It covers key topics such as census versus sample surveys, sampling design, steps in sampling design including defining the population, sampling unit, sample size, and sampling procedure. Factors that could lead to systematic bias are also outlined. The goal in selecting a sampling procedure is to minimize both systematic bias and sampling error while considering costs. Choosing an appropriate sampling technique is an important part of developing a reliable research methodology.
Research methodology, design, meaning, features, need, Sampling, errors in su...Prashant Ranjan
The document discusses research design and methodology. It defines research design and outlines its key features and needs. It describes different types of research designs including exploratory, descriptive, diagnostic, and hypothesis testing. It also discusses sampling, including probability and non-probability sampling. Finally, it covers potential errors in surveys such as sampling errors and non-sampling errors.
This document discusses quantitative research methods. It explains that quantitative research aims to quantify and measure social phenomena numerically in order to examine relationships between variables statistically. Some key points covered include:
- Quantitative research methods include surveys, experiments, and analyzing numerical data. Surveys can be administered in-person, by phone, mail, or online.
- Closed-ended questions are easier to analyze but may limit responses, while open-ended questions provide more flexibility but are harder to analyze.
- Various survey methods like in-person, phone, and mail have different strengths and weaknesses in terms of cost, response rates, and control. Experimental research assigns participants to groups to study causal relationships.
MEANING OF RESEARCH
OBJECTIVES OF RESEARCH
CHARACTERISTICS OF RESEARCH
CRITERIA OF A GOOD RESEARCH
QUALITIES OF GOOD RESEARCH
RESEARCH MOTIVATIONS
TYPES OF RESEARCH
PROBLEMS IN RESEARCH
RESEARCH APPROACHES
RESEARCH PROCESS
LITERATURE REVIEW
HYPOTHESIS
CRITERIA OF GOOD RESEARCH
PROBLEMS ENCOUNTERED BY RESEARCHER
Learn the process of Research.
Research process consists of a series of actions or steps necessary to carry out research. It guides a researcher to conduct research in a planned and organized sequence.
The document provides an overview of survey research and questionnaire design. It discusses that surveys are used to collect data and facts from a target population about a certain situation or issue. The key steps in survey research include developing hypotheses, designing the survey questions and format, sampling, data collection, analysis, and reporting findings. It also describes different types of surveys, methods of data collection including mail, interview and telephone surveys, and considerations for question structure, format, and response options. The document emphasizes that carefully designing and testing the questionnaire is important for effective survey research.
Samples are used in research studies to represent larger populations. While studying the entire population would provide the best data, samples are smaller and less expensive. Researchers define both the target population they wish to generalize to and the accessible population they can actually study. Random sampling involves chance to select participants while nonrandom sampling selects participants based on specific characteristics. Common sampling techniques include simple random, stratified, cluster, systematic, and convenience sampling.
Research Challenges - Characteristics of a Good Researcher Dr. Mazlan Abbas
This document discusses characteristics of good researchers and challenges in research. It provides definitions of basic and applied research, explaining that basic research expands knowledge while applied research solves practical problems. It also distinguishes between degrees (Bachelor's), Masters, and PhDs, illustrating how each level deepens knowledge in a specialty area. The document notes that choosing a good research problem takes time and is subjective. It also outlines common research approaches like mathematical modeling, simulation, and experimentation, and discusses managing researchers and their expectations around creativity and knowledge generation.
The document provides information on various sampling techniques used in research. It defines key terms like population, sample, sampling, and element. It describes different probability sampling techniques like simple random sampling, stratified random sampling, systematic random sampling, and cluster sampling. It also covers non-probability sampling techniques such as purposive sampling and convenience sampling. The document discusses the purposes, processes, merits, and limitations of different sampling methods.
Research is defined as a systematic effort to gain new knowledge. It involves formulating a research problem, conducting a literature review, developing hypotheses, designing a study, collecting and analyzing data, and reporting findings. The goal of research is to discover answers to questions through objective and systematic methods of finding solutions.
The document discusses the meaning, objectives, characteristics, types, and steps of research. It defines research as a systematic, directed search for knowledge. The main objectives of research are to gain new insights or accurately describe characteristics. Research is characterized by careful investigation and testing of conclusions. The main types discussed are descriptive, analytical, applied, fundamental, quantitative, and qualitative research. Key steps include formulating the problem, reviewing literature, developing hypotheses, collecting and analyzing data, and reporting findings. Research design involves determining what, why, where, when of a study. It is important for testing hypotheses and controlling for extraneous variables.
Foundations of Agricultural Research by Prof Jayne MugweJayne Mugwe
This PPT presentation gives overview of Agricultural Research. Explains meaning of scientifc research, Characteristics of research, research process at a glance, Importance of research and research development continnum
Prof Jayne Mugwe
Kenyatta University
This document provides information about research methodology. It begins by defining what research is, noting that research is a systematic process of finding answers to questions through a search for truth and new knowledge. The document then discusses what can be classified as research through some examples. It also covers the research process, which involves defining the problem, reviewing literature, formulating objectives and hypotheses, designing the methodology, collecting and analyzing data, and reporting findings. Additional topics covered include the purpose of reviewing literature, identifying a research problem, and recording literature through source cards and note cards.
The document outlines the scientific research method and provides guidance on developing mathematical models and completing a thesis. It describes the four main steps of the scientific method as observation, hypothesis, experimental testing, and predictions. Observation involves recognizing facts or occurrences, which are then used to form a hypothesis. The hypothesis is then tested experimentally, and if proven true, predictions can be made. Mathematical models, such as using equations to fit experimental data, can help test hypotheses and predictions. Following the scientific method and reporting iterations that include publishable results are keys to completing a successful thesis.
This document discusses different types of study designs used in medical research, including qualitative and quantitative methods. It covers observational studies like cohort and case-control studies, as well as experimental designs like randomized controlled trials. For each study type, it outlines their purpose, strengths, weaknesses and the types of research questions they can help answer. The goal is to help researchers choose the most appropriate design based on their specific research question and aims.
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then distinguishes between probability sampling methods, like simple random sampling, systematic sampling, and stratified sampling, and non-probability sampling methods. For each method, it provides details on how the sampling is conducted and notes advantages and disadvantages. The goal is to help readers understand different approaches to collecting representative samples from a population in a way that allows results to be generalized.
This document discusses different sampling methods used in research. It begins by defining sampling as selecting a subset of units from a larger population. The document then covers probability sampling methods like simple random sampling, systematic sampling, and stratified sampling. It also discusses non-probability sampling and provides examples. For each method, it describes how to implement the technique and highlights advantages and disadvantages. The key goal is to help readers understand how to appropriately select samples to gather data about a target population.
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then covers different types of sampling, distinguishing between probability sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling, and non-probability sampling methods like convenience sampling. For each method, it provides details on how to implement it and notes advantages and disadvantages. The document aims to help readers understand different sampling techniques and how to select the appropriate method for their research needs.
This document discusses different sampling methods used in research. It begins by defining sampling as selecting a subset of a population to make inferences about the whole population. The document then covers probability sampling methods like simple random sampling, systematic sampling, and stratified sampling. It also discusses non-probability sampling and provides examples. Key advantages and disadvantages of each method are described.
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then covers different types of sampling, distinguishing between probability sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling, and non-probability sampling methods like convenience sampling. For each method, it provides details on how to implement it and notes advantages and disadvantages. The document aims to help readers understand different sampling techniques and how to select the appropriate method for their research needs.
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then covers different types of sampling, distinguishing between probability sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling, and non-probability sampling methods like convenience sampling. For each method, it provides details on how to implement it and notes advantages and disadvantages. The document aims to help readers understand sampling techniques and how to select the appropriate method for their research needs.
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then explains the difference between probability sampling methods, like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling, and non-probability sampling methods, like convenience sampling. For each method, it provides details on how to implement the method and discusses their relative advantages and disadvantages. The goal is to help readers understand different approaches to drawing sample populations from a target population in a way that limits bias.
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then covers different types of sampling, distinguishing between probability sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling, and non-probability sampling methods like convenience sampling. For each method, it provides details on how to implement it and notes advantages and disadvantages. The document aims to help readers understand different sampling techniques and how to select the appropriate method for their research needs.
This document discusses different sampling methods used in research. It begins by defining sampling as selecting a subset of a population to make inferences about the whole population. The document then covers probability sampling methods like simple random sampling, systematic sampling, and stratified sampling. It also discusses non-probability sampling and provides examples. For each method, it describes the process, advantages, and disadvantages. The key goal is to help readers understand how to select representative samples for research studies.
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then distinguishes between probability sampling methods, like simple random sampling, systematic sampling, and stratified sampling, and non-probability sampling methods. For each method, it provides details on how the sampling is conducted and advantages and disadvantages. Cluster sampling is also explained as a multi-stage process where clusters rather than individuals are selected.
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then distinguishes between probability sampling methods, like simple random sampling, systematic sampling, and stratified sampling, and non-probability sampling methods. For each method, it provides details on how the sampling is conducted and advantages and disadvantages. Cluster sampling is also explained as a multi-stage process where clusters rather than individuals are selected.
This document discusses various sampling methods used in research. It begins by defining a sample and explaining why sampling is used instead of surveying entire populations. The document then distinguishes between probability sampling methods, which assign a known probability of selection to each unit, and non-probability sampling methods, which do not. Specific probability methods covered include simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling. Non-probability methods discussed are convenience sampling and purposive sampling. Advantages and disadvantages of each approach are provided.
Phyton class by Pavan - Study notes inclPavan Babu .G
This document discusses different sampling methods used in research. It begins by defining sampling as selecting a subset of a population to make inferences about the whole population. The document then covers various probability sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling. It also discusses non-probability sampling and compares the advantages and disadvantages of different sampling techniques. Key factors that influence sample representativeness like sampling procedure, sample size, and response rate are also highlighted.
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then covers different types of sampling, distinguishing between probability sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling, and non-probability sampling methods like convenience sampling. For each method, it provides brief explanations of the process and notes advantages and disadvantages. The document aims to help readers understand different sampling techniques and how to select the appropriate method for their research needs.
Methods of Sampling used in dentistry. pptswarnimakhichi
This document discusses various sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then describes different types of sampling, including probability sampling methods like simple random sampling, systematic sampling, and stratified sampling, as well as non-probability sampling methods. For each method, it provides details on the process and discusses their relative advantages and disadvantages. The document aims to help readers understand sampling and how to select the appropriate technique for their research.
The document discusses various sampling methods and concepts in research methodology. It defines key terms like population, sample, sampling frame, probability sampling, and non-probability sampling. It then explains different probability sampling techniques like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling. It also discusses non-probability sampling methods and compares the advantages and disadvantages of different approaches. The document emphasizes the importance of representative sampling.
This document discusses different sampling methods used in research. It defines key terms like population, sample, and sampling frame. It explains the difference between probability and non-probability sampling. Some common probability sampling methods described include simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling. Non-probability sampling methods mentioned are convenience sampling and purposive sampling. The document provides details on how each sampling method is implemented and their relative advantages and disadvantages.
This document provides an overview of different sampling methods used in research. It begins by defining key terms like population, sample, and sampling frame. It then distinguishes between probability sampling methods, like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multistage sampling, and non-probability sampling methods, like convenience sampling. For each method, it discusses how the sample is selected and the relative advantages and disadvantages. The document aims to help readers understand why sampling is necessary, different sampling techniques, and how to select the appropriate method for their research needs.
The document discusses how modern life has brought more possessions and conveniences but less quality time and community. It notes we have bigger houses but smaller families, more knowledge but less wisdom, and more health issues despite medical advances. It encourages the reader to make every day meaningful by spending time with loved ones, enjoying favorite activities, and expressing gratitude and love. The overall message is to focus on experiences and relationships rather than material things.
Tribal people in India are known as adivasi, which refers to the original inhabitants of a region. There are over 573 recognized tribes that receive government benefits. Tribes make up roughly 75% of the total tribal population and are most prominent in central Indian states. While tribes traditionally enjoyed autonomy, British colonization disrupted this and autonomy has not been fully restored. The tribal belt spans central and northeast India and is home to 81 million indigenous people whose ancestors may have inhabited India before Aryan invaders arrived around 1500 BC. This region remains one of India's most impoverished areas as tribes face loss of forest land and difficulties cultivating fields.
The Kadu Kuruba are an indigenous tribe that has historically lived in the forest regions of Karnataka, India. They speak Kannada and Kuruba, and have lived in these forests for centuries. However, in the early 1970s, they were forcibly evicted from their ancestral lands in the forests and forced to live on the outskirts, lacking land rights. As a result, they remain marginalized. The Kadu Kuruba practice Hinduism and worship stones and ancestors. They were traditionally experts in forest skills like basket weaving but now many work as daily laborers due to loss of land and resources.
The Kadu Kuruba are the original inhabitants of the forests of southern India. They developed their own culture and traditions due to prolonged isolation in the forests. In the early 1970s, they were forcibly evicted from their ancestral lands and forced to live on the outskirts of the forest, lacking land rights and remaining marginalized.
The document discusses tribes in India, including their origins, characteristics, constitutional protections, and population statistics. It defines tribes as groups that share a common name, territory, language, occupation, and culture. The Indian constitution recognizes over 255 tribes across 17 states as Scheduled Tribes and grants them protections and development safeguards. According to the 2011 census, there are over 10 crore tribal people in India, mostly living in isolated rural areas across all states except a few. The document also provides details about the Jenu Kuruba tribe and tribal population ratios in Karnataka.
This document provides census data on housing conditions and assets in slums in India and the state of Karnataka. Some key findings are:
- In India, there are over 137 million slum households, with the largest percentages in Maharashtra, Andhra Pradesh, and Tamil Nadu.
- In India, 58% of slum houses are considered to be in "good" condition, 38% "livable", and 4% "dilapidated".
- The most common materials for roofs in Indian slum houses are GI/metal sheets (26%), concrete (36%), and tiles (16%). The most common wall materials are burnt brick (59%) and mud (14%).
CapTechTalks Webinar Slides June 2024 Donovan Wright.pptxCapitolTechU
Slides from a Capitol Technology University webinar held June 20, 2024. The webinar featured Dr. Donovan Wright, presenting on the Department of Defense Digital Transformation.
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
How to Manage Reception Report in Odoo 17Celine George
A business may deal with both sales and purchases occasionally. They buy things from vendors and then sell them to their customers. Such dealings can be confusing at times. Because multiple clients may inquire about the same product at the same time, after purchasing those products, customers must be assigned to them. Odoo has a tool called Reception Report that can be used to complete this assignment. By enabling this, a reception report comes automatically after confirming a receipt, from which we can assign products to orders.
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...indexPub
The recent surge in pro-Palestine student activism has prompted significant responses from universities, ranging from negotiations and divestment commitments to increased transparency about investments in companies supporting the war on Gaza. This activism has led to the cessation of student encampments but also highlighted the substantial sacrifices made by students, including academic disruptions and personal risks. The primary drivers of these protests are poor university administration, lack of transparency, and inadequate communication between officials and students. This study examines the profound emotional, psychological, and professional impacts on students engaged in pro-Palestine protests, focusing on Generation Z's (Gen-Z) activism dynamics. This paper explores the significant sacrifices made by these students and even the professors supporting the pro-Palestine movement, with a focus on recent global movements. Through an in-depth analysis of printed and electronic media, the study examines the impacts of these sacrifices on the academic and personal lives of those involved. The paper highlights examples from various universities, demonstrating student activism's long-term and short-term effects, including disciplinary actions, social backlash, and career implications. The researchers also explore the broader implications of student sacrifices. The findings reveal that these sacrifices are driven by a profound commitment to justice and human rights, and are influenced by the increasing availability of information, peer interactions, and personal convictions. The study also discusses the broader implications of this activism, comparing it to historical precedents and assessing its potential to influence policy and public opinion. The emotional and psychological toll on student activists is significant, but their sense of purpose and community support mitigates some of these challenges. However, the researchers call for acknowledging the broader Impact of these sacrifices on the future global movement of FreePalestine.
Elevate Your Nonprofit's Online Presence_ A Guide to Effective SEO Strategies...TechSoup
Whether you're new to SEO or looking to refine your existing strategies, this webinar will provide you with actionable insights and practical tips to elevate your nonprofit's online presence.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
🔥🔥🔥🔥🔥🔥🔥🔥🔥
إضغ بين إيديكم من أقوى الملازم التي صممتها
ملزمة تشريح الجهاز الهيكلي (نظري 3)
💀💀💀💀💀💀💀💀💀💀
تتميز هذهِ الملزمة بعِدة مُميزات :
1- مُترجمة ترجمة تُناسب جميع المستويات
2- تحتوي على 78 رسم توضيحي لكل كلمة موجودة بالملزمة (لكل كلمة !!!!)
#فهم_ماكو_درخ
3- دقة الكتابة والصور عالية جداً جداً جداً
4- هُنالك بعض المعلومات تم توضيحها بشكل تفصيلي جداً (تُعتبر لدى الطالب أو الطالبة بإنها معلومات مُبهمة ومع ذلك تم توضيح هذهِ المعلومات المُبهمة بشكل تفصيلي جداً
5- الملزمة تشرح نفسها ب نفسها بس تكلك تعال اقراني
6- تحتوي الملزمة في اول سلايد على خارطة تتضمن جميع تفرُعات معلومات الجهاز الهيكلي المذكورة في هذهِ الملزمة
واخيراً هذهِ الملزمة حلالٌ عليكم وإتمنى منكم إن تدعولي بالخير والصحة والعافية فقط
كل التوفيق زملائي وزميلاتي ، زميلكم محمد الذهبي 💊💊
🔥🔥🔥🔥🔥🔥🔥🔥🔥
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
How to Download & Install Module From the Odoo App Store in Odoo 17Celine George
Custom modules offer the flexibility to extend Odoo's capabilities, address unique requirements, and optimize workflows to align seamlessly with your organization's processes. By leveraging custom modules, businesses can unlock greater efficiency, productivity, and innovation, empowering them to stay competitive in today's dynamic market landscape. In this tutorial, we'll guide you step by step on how to easily download and install modules from the Odoo App Store.
2. LEARNING OBJECTIVES
Learn the reasons for sampling
Develop an understanding about different sampling methods
Distinguish between probability & non probability sampling
Discuss the relative advantages & disadvantages of each sampling
methods
2
3. What is research?
• “Scientific research is systematic, controlled, empirical,
and critical investigation of natural phenomena guided by
theory and hypotheses about the presumed relations
among such phenomena.”
– Kerlinger, 1986
• Research is an organized and systematic way of finding
answers to questions
3
4. Important Components of Empirical Research
Problem statement, research questions, purposes, benefits
Theory, assumptions, background literature
Variables and hypotheses
Operational definitions and measurement
Research design and methodology
Instrumentation, sampling
Data analysis
Conclusions, interpretations, recommendations
4
5. SAMPLING
A sample is “a smaller (but hopefully
representative) collection of units from a
population used to determine truths about that
population” (Field, 2005)
Why sample?
Resources (time, money) and workload
Gives results with known accuracy that can be
calculated mathematically
The sampling frame is the list from which the
potential respondents are drawn
Registrar’s office
Class rosters
Must assess sampling frame errors
5
6. SAMPLING……
What is your population of interest?
To whom do you want to generalize your
results?
All doctors
School children
Indians
Women aged 15-45 years
Other
Can you sample the entire population?
6
7. SAMPLING…….
3 factors that influence sample representative-
ness
Sampling procedure
Sample size
Participation (response)
When might you sample the entire population?
When your population is very small
When you have extensive resources
When you don’t expect a very high response
7
8. Types of Samples
Probability (Random) Samples
Simple random sample
Systematic random sample
Stratified random sample
Multistage sample
Multiphase sample
Cluster sample
Non-Probability Samples
Convenience sample
Purposive sample
Quota
8
9. Process
The sampling process comprises several stages:
Defining the population of concern
Specifying a sampling frame, a set of items or
events possible to measure
Specifying a sampling method for selecting
items or events from the frame
Determining the sample size
Implementing the sampling plan
Sampling and data collecting
Reviewing the sampling process
9
10. Population definition
A population can be defined as including all
people or items with the characteristic one
wishes to understand.
Because there is very rarely enough time or
money to gather information from everyone
or everything in a population, the goal
becomes finding a representative sample (or
subset) of that population.
10
11. Population definition…….
Note also that the population from which the sample is drawn may not be
the same as the population about which we actually want information. Often
there is large but not complete overlap between these two groups due to
frame issues etc .
Sometimes they may be entirely separate - for instance, we might study
rats in order to get a better understanding of human health, or we might
study records from people born in 2008 in order to make predictions about
people born in 2009.
11
12. SAMPLING FRAME
In the most straightforward case, such as the
sentencing of a batch of material from production
(acceptance sampling by lots), it is possible to
identify and measure every single item in the
population and to include any one of them in our
sample. However, in the more general case this is not
possible. There is no way to identify all rats in the
set of all rats. Where voting is not compulsory,
there is no way to identify which people will actually
vote at a forthcoming election (in advance of the
election)
As a remedy, we seek a sampling frame which has
the property that we can identify every single
element and include any in our sample .
The sampling frame must be representative of the
population
12
13. PROBABILITY SAMPLING
A probability sampling scheme is one in which every
unit in the population has a chance (greater than
zero) of being selected in the sample, and this
probability can be accurately determined.
. When every element in the population does have the
same probability of selection, this is known as an
'equal probability of selection' (EPS) design. Such
designs are also referred to as 'self-weighting'
because all sampled units are given the same weight.
13
14. PROBABILITY SAMPLING…….
Probability sampling includes:
Simple Random Sampling,
Systematic Sampling,
Stratified Random Sampling,
Cluster Sampling
Multistage Sampling.
Multiphase sampling
14
15. NON PROBABILITY SAMPLING
Any sampling method where some elements of population
have no chance of selection (these are sometimes
referred to as 'out of coverage'/'undercovered'), or
where the probability of selection can't be accurately
determined. It involves the selection of elements based
on assumptions regarding the population of interest,
which forms the criteria for selection. Hence, because
the selection of elements is nonrandom, nonprobability
sampling not allows the estimation of sampling errors..
Example: We visit every household in a given street, and
interview the first person to answer the door. In any
household with more than one occupant, this is a
nonprobability sample, because some people are more
likely to answer the door (e.g. an unemployed person who
spends most of their time at home is more likely to
answer than an employed housemate who might be at
work when the interviewer calls) and it's not practical to
calculate these probabilities.
15
16. NONPROBABILITY SAMPLING…….
• Nonprobability Sampling includes: Accidental
Sampling, Quota Sampling and Purposive Sampling. In
addition, nonresponse effects may turn any
probability design into a nonprobability design if the
characteristics of nonresponse are not well
understood, since nonresponse effectively modifies
each element's probability of being sampled.
16
17. SIMPLE RANDOM SAMPLING
• Applicable when population is small, homogeneous & readily available
• All subsets of the frame are given an equal probability. Each element of the
frame thus has an equal probability of selection.
• It provides for greatest number of possible samples. This is done by
assigning a number to each unit in the sampling frame.
• A table of random number or lottery system is used to determine which
units are to be selected.
17
18. SIMPLE RANDOM SAMPLING……..
Estimates are easy to calculate.
Simple random sampling is always an EPS design, but not all
EPS designs are simple random sampling.
Disadvantages
If sampling frame large, this method impracticable.
Minority subgroups of interest in population may not be
present in sample in sufficient numbers for study.
18
19. REPLACEMENT OF SELECTED UNITS
Sampling schemes may be without replacement ('WOR' - no element can be
selected more than once in the same sample) or with replacement ('WR' - an
element may appear multiple times in the one sample).
For example, if we catch fish, measure them, and immediately return them
to the water before continuing with the sample, this is a WR design,
because we might end up catching and measuring the same fish more than
once. However, if we do not return the fish to the water (e.g. if we eat the
fish), this becomes a WOR design.
19
20. SYSTEMATIC SAMPLING
Systematic sampling relies on arranging the target
population according to some ordering scheme and then
selecting elements at regular intervals through that
ordered list.
Systematic sampling involves a random start and then
proceeds with the selection of every kth element from
then onwards. In this case, k=(population size/sample
size).
It is important that the starting point is not
automatically the first in the list, but is instead
randomly chosen from within the first to the kth
element in the list.
A simple example would be to select every 10th name
from the telephone directory (an 'every 10th' sample,
also referred to as 'sampling with a skip of 10').
20
21. SYSTEMATIC SAMPLING……
As described above, systematic sampling is an EPS method, because all
elements have the same probability of selection (in the example
given, one in ten). It is not 'simple random sampling' because
different subsets of the same size have different selection
probabilities - e.g. the set {4,14,24,...,994} has a one-in-ten
probability of selection, but the set {4,13,24,34,...} has zero
probability of selection.
21
22. SYSTEMATIC SAMPLING……
ADVANTAGES:
Sample easy to select
Suitable sampling frame can be identified easily
Sample evenly spread over entire reference population
DISADVANTAGES:
Sample may be biased if hidden periodicity in population
coincides with that of selection.
Difficult to assess precision of estimate from one survey.
22
23. STRATIFIED SAMPLING
Where population embraces a number of distinct categories, the frame can
be organized into separate "strata." Each stratum is then sampled as an
independent sub-population, out of which individual elements can be
randomly selected.
Every unit in a stratum has same chance of being selected.
Using same sampling fraction for all strata ensures proportionate
representation in the sample.
Adequate representation of minority subgroups of interest can be ensured
by stratification & varying sampling fraction between strata as required.
23
24. STRATIFIED SAMPLING……
Finally, since each stratum is treated as an independent population,
different sampling approaches can be applied to different strata.
Drawbacks to using stratified sampling.
First, sampling frame of entire population has to be prepared
separately for each stratum
Second, when examining multiple criteria, stratifying variables may be
related to some, but not to others, further complicating the design, and
potentially reducing the utility of the strata.
Finally, in some cases (such as designs with a large number of strata, or
those with a specified minimum sample size per group), stratified
sampling can potentially require a larger sample than would other
methods
24
26. POSTSTRATIFICATION
Stratification is sometimes introduced after the sampling phase in a process
called "poststratification“.
This approach is typically implemented due to a lack of prior knowledge of an
appropriate stratifying variable or when the experimenter lacks the necessary
information to create a stratifying variable during the sampling phase. Although
the method is susceptible to the pitfalls of post hoc approaches, it can provide
several benefits in the right situation. Implementation usually follows a simple
random sample. In addition to allowing for stratification on an ancillary variable,
poststratification can be used to implement weighting, which can improve the
precision of a sample's estimates.
26
27. OVERSAMPLING
Choice-based sampling is one of the stratified
sampling strategies. In this, data are stratified on
the target and a sample is taken from each strata so
that the rare target class will be more represented in
the sample. The model is then built on this biased
sample. The effects of the input variables on the
target are often estimated with more precision with
the choice-based sample even when a smaller overall
sample size is taken, compared to a random sample.
The results usually must be adjusted to correct for
the oversampling.
27
28. CLUSTER SAMPLING
Cluster sampling is an example of 'two-stage
sampling' .
First stage a sample of areas is chosen;
Second stage a sample of respondents within
those areas is selected.
Population divided into clusters of homogeneous
units, usually based on geographical contiguity.
Sampling units are groups rather than individuals.
A sample of such clusters is then selected.
All units from the selected clusters are studied.
28
29. CLUSTER SAMPLING…….
Advantages :
Cuts down on the cost of preparing a sampling frame.
This can reduce travel and other administrative costs.
Disadvantages: sampling error is higher for a simple
random sample of same size.
Often used to evaluate vaccination coverage in EPI
29
30. CLUSTER SAMPLING…….
• Identification of clusters
– List all cities, towns, villages & wards of cities with their population falling in
target area under study.
– Calculate cumulative population & divide by 30, this gives sampling interval.
– Select a random no. less than or equal to sampling interval having same no. of
digits. This forms 1st
cluster.
– Random no.+ sampling interval = population of 2nd
cluster.
– Second cluster + sampling interval = 4th
cluster.
– Last or 30th
cluster = 29th
cluster + sampling interval
30
31. CLUSTER SAMPLING…….
Two types of cluster sampling methods.
One-stage sampling. All of the elements within selected
clusters are included in the sample.
Two-stage sampling. A subset of elements within
selected clusters are randomly selected for inclusion
in the sample.
31
32. CLUSTER SAMPLING…….
• Freq c f cluster
• I 2000 2000 1
• II 3000 5000 2
• III 1500 6500
• IV 4000 10500 3
• V 5000 15500 4, 5
• VI 2500 18000 6
• VII 2000 20000 7
• VIII 3000 23000 8
• IX 3500 26500 9
• X 4500 31000 10
• XI 4000 35000 11, 12
• XII 4000 39000 13
• XIII 3500 44000 14,15
• XIV 2000 46000
• XV 3000 49000 16
• XVI 3500 52500 17
• XVII 4000 56500 18,19
• XVIII 4500 61000 20
• XIX 4000 65000 21,22
• XX 4000 69000 23
• XXI 2000 71000 24
• XXII 2000 73000
• XXIII 3000 76000 25
• XXIV 3000 79000 26
• XXV 5000 84000 27,28
• XXVI 2000 86000 29
• XXVII 1000 87000
• XXVIII 1000 88000
• XXIX 1000 89000 30
• XXX 1000 90000
• 90000/30 = 3000 sampling interval
32
33. Difference Between Strata and Clusters
Although strata and clusters are both non-overlapping
subsets of the population, they differ in several ways.
All strata are represented in the sample; but only a
subset of clusters are in the sample.
With stratified sampling, the best survey results
occur when elements within strata are internally
homogeneous. However, with cluster sampling, the
best results occur when elements within clusters are
internally heterogeneous
33
34. MULTISTAGE SAMPLING
Complex form of cluster sampling in which two or more levels of
units are embedded one in the other.
First stage, random number of districts chosen in all
states.
Followed by random number of talukas, villages.
Then third stage units will be houses.
All ultimate units (houses, for instance) selected at last step
are surveyed.
34
35. MULTISTAGE SAMPLING……..
This technique, is essentially the process of taking
random samples of preceding random samples.
Not as effective as true random sampling, but
probably solves more of the problems inherent to
random sampling.
An effective strategy because it banks on multiple
randomizations. As such, extremely useful.
Multistage sampling used frequently when a
complete list of all members of the population not
exists and is inappropriate.
Moreover, by avoiding the use of all sample units in
all selected clusters, multistage sampling avoids the
large, and perhaps unnecessary, costs associated
with traditional cluster sampling.
35
36. MULTI PHASE SAMPLING
Part of the information collected from whole sample & part from
subsample.
In Tb survey MT in all cases – Phase I
X –Ray chest in MT +ve cases – Phase II
Sputum examination in X – Ray +ve cases - Phase III
Survey by such procedure is less costly, less laborious & more
purposeful
36
37. MATCHED RANDOM SAMPLING
A method of assigning participants to groups in which
pairs of participants are first matched on some
characteristic and then individually assigned randomly to
groups.
The Procedure for Matched random sampling can be
briefed with the following contexts,
Two samples in which the members are clearly paired, or
are matched explicitly by the researcher. For example,
IQ measurements or pairs of identical twins.
Those samples in which the same attribute, or variable,
is measured twice on each subject, under different
circumstances. Commonly called repeated measures.
Examples include the times of a group of athletes for
1500m before and after a week of special training; the
milk yields of cows before and after being fed a
particular diet.
37
38. QUOTA SAMPLING
The population is first segmented into mutually exclusive
sub-groups, just as in stratified sampling.
Then judgment used to select subjects or units from
each segment based on a specified proportion.
For example, an interviewer may be told to sample 200
females and 300 males between the age of 45 and 60.
It is this second step which makes the technique one of
non-probability sampling.
In quota sampling the selection of the sample is non-
random.
For example interviewers might be tempted to interview
those who look most helpful. The problem is that these
samples may be biased because not everyone gets a
chance of selection. This random element is its greatest
weakness and quota versus probability has been a matter
of controversy for many years
38
39. CONVENIENCE SAMPLING
Sometimes known as grab or opportunity sampling or accidental
or haphazard sampling.
A type of nonprobability sampling which involves the sample being
drawn from that part of the population which is close to hand.
That is, readily available and convenient.
The researcher using such a sample cannot scientifically make
generalizations about the total population from this sample
because it would not be representative enough.
For example, if the interviewer was to conduct a survey at a
shopping center early in the morning on a given day, the people
that he/she could interview would be limited to those given there
at that given time, which would not represent the views of other
members of society in such an area, if the survey was to be
conducted at different times of day and several times per week.
This type of sampling is most useful for pilot testing.
In social science research, snowball sampling is a similar technique,
where existing study subjects are used to recruit more subjects
into the sample.
39
41. Judgmental sampling or Purposive
sampling
- The researcher chooses the sample based on who
they think would be appropriate for the study. This is
used primarily when there is a limited number of
people that have expertise in the area being
researched
41
42. PANEL SAMPLING
Method of first selecting a group of participants through a
random sampling method and then asking that group for the same
information again several times over a period of time.
Therefore, each participant is given same survey or interview at
two or more time points; each period of data collection called a
"wave".
This sampling methodology often chosen for large scale or
nation-wide studies in order to gauge changes in the population
with regard to any number of variables from chronic illness to job
stress to weekly food expenditures.
Panel sampling can also be used to inform researchers about
within-person health changes due to age or help explain changes
in continuous dependent variables such as spousal interaction.
There have been several proposed methods of analyzing panel
sample data, including growth curves.
42
44. What sampling method u recommend?
Determining proportion of undernourished five year olds in a village.
Investigating nutritional status of preschool children.
Selecting maternity records for the study of previous abortions or duration
of postnatal stay.
In estimation of immunization coverage in a province, data on seven children
aged 12-23 months in 30 clusters are used to determine proportion of fully
immunized children in the province.
Give reasons why cluster sampling is used in this survey.
44
45. Probability proportional to size
sampling In some cases the sample designer has access to
an "auxiliary variable" or "size measure", believed to
be correlated to the variable of interest, for each
element in the population. This data can be used
to improve accuracy in sample design. One option
is to use the auxiliary variable as a basis for
stratification, as discussed above.
Another option is probability-proportional-to-size
('PPS') sampling, in which the selection probability
for each element is set to be proportional to its size
measure, up to a maximum of 1. In a simple PPS
design, these selection probabilities can then be
used as the basis for Poisson sampling. However,
this has the drawbacks of variable sample size, and
different portions of the population may still be
over- or under-represented due to chance
variation in selections. To address this problem, PPS
may be combined with a systematic approach.
45
46. Contd. Example: Suppose we have six schools with populations of
150, 180, 200, 220, 260, and 490 students respectively (total
1500 students), and we want to use student population as
the basis for a PPS sample of size three. To do this, we could
allocate the first school numbers 1 to 150, the second
school 151 to 330 (= 150 + 180), the third school 331 to 530,
and so on to the last school (1011 to 1500). We then
generate a random start between 1 and 500 (equal
to 1500/3) and count through the school populations by
multiples of 500. If our random start was 137, we would
select the schools which have been allocated numbers
137, 637, and 1137, i.e. the first, fourth, and sixth schools.
The PPS approach can improve accuracy for a given
sample size by concentrating sample on large elements
that have the greatest impact on population estimates. PPS
sampling is commonly used for surveys of businesses, where
element size varies greatly and auxiliary information is often
available - for instance, a survey attempting to measure
the number of guest-nights spent in hotels might use each
hotel's number of rooms as an auxiliary variable. In some
cases, an older measurement of the variable of interest
can be used as an auxiliary variable when attempting to
produce more current estimates.
46
47. Event sampling
Event Sampling Methodology (ESM) is a new form of sampling
method that allows researchers to study ongoing experiences
and events that vary across and within days in its naturally-
occurring environment. Because of the frequent sampling of
events inherent in ESM, it enables researchers to measure the
typology of activity and detect the temporal and dynamic
fluctuations of work experiences. Popularity of ESM as a new
form of research design increased over the recent years
because it addresses the shortcomings of cross-sectional
research, where once unable to, researchers can now detect
intra-individual variances across time. In ESM, participants are
asked to record their experiences and perceptions in a paper
or electronic diary.
There are three types of ESM:# Signal contingent – random
beeping notifies participants to record data. The advantage
of this type of ESM is minimization of recall bias.
Event contingent – records data when certain events occur
47
48. Contd.
Event contingent – records data when certain events
occur
Interval contingent – records data according to the
passing of a certain period of time
ESM has several disadvantages. One of the
disadvantages of ESM is it can sometimes be
perceived as invasive and intrusive by participants.
ESM also leads to possible self-selection bias. It may be
that only certain types of individuals are willing to
participate in this type of study creating a non-random
sample. Another concern is related to participant
cooperation. Participants may not be actually fill out
their diaries at the specified times. Furthermore, ESM
may substantively change the phenomenon being
studied. Reactivity or priming effects may occur, such
that repeated measurement may cause changes in
the participants' experiences. This method of sampling
data is also highly vulnerable to common method
variance.[6]
48
49. contd.
Further, it is important to think about whether
or not an appropriate dependent variable is
being used in an ESM design. For example, it
might be logical to use ESM in order to answer
research questions which involve dependent
variables with a great deal of variation
throughout the day. Thus, variables such as
change in mood, change in stress level, or the
immediate impact of particular events may be
best studied using ESM methodology.
However, it is not likely that utilizing ESM will
yield meaningful predictions when measuring
someone performing a repetitive task
throughout the day or when dependent
variables are long-term in nature (coronary
heart problems).
49
Editor's Notes
PROBLEM STATEMENT, PURPOSES, BENEFITS
What exactly do I want to find out?
What is a researchable problem?
What are the obstacles in terms of knowledge, data availability, time, or resources?
Do the benefits outweigh the costs?
THEORY, ASSUMPTIONS, BACKGROUND LITERATURE
What does the relevant literature in the field indicate about this problem?
Which theory or conceptual framework does the work fit within?
What are the criticisms of this approach, or how does it constrain the research process?
What do I know for certain about this area?
What is the background to the problem that needs to be made available in reporting the work?
VARIABLES AND HYPOTHESES
What will I take as given in the environment ie what is the starting point?
Which are the independent and which are the dependent variables?
Are there control variables?
Is the hypothesis specific enough to be researchable yet still meaningful?
How certain am I of the relationship(s) between variables?
OPERATIONAL DEFINITIONS AND MEASUREMENT
Does the problem need scoping/simplifying to make it achievable?
What and how will the variables be measured?
What degree of error in the findings is tolerable?
Is the approach defendable?
RESEARCH DESIGN AND METHODOLOGY
What is my overall strategy for doing this research?
Will this design permit me to answer the research question?
What constraints will the approach place on the work?
INSTRUMENTATION/SAMPLING
How will I get the data I need to test my hypothesis?
What tools or devices will I use to make or record observations?
Are valid and reliable instruments available, or must I construct my own?
How will I choose the sample?
Am I interested in representativeness?
If so, of whom or what, and with what degree of accuracy or level of confidence?
DATA ANALYSIS
What combinations of analytical and statistical process will be applied to the data?
Which of these will allow me to accept or reject my hypotheses?
Do the findings show numerical differences, and are those differences important?
CONCLUSIONS, INTERPRETATIONS, RECOMMENDATIONS
Was my initial hypothesis supported?
What if my findings are negative?
What are the implications of my findings for the theory base, for the background assumptions, or relevant literature?
What recommendations result from the work?
What suggestions can I make for further research on this topic?
Sampling frame errors: university versus personal email addresses; changing class rosters; are all students in your population of interest represented?
How do we determine our population of interest?
Administrators can tell us
We notice anecdotally or through qualitative research that a particular subgroup of students is experiencing higher risk
We decide to do everyone and go from there
3 factors that influence sample representativeness
Sampling procedure
Sample size
Participation (response)
When might you sample the entire population?
When your population is very small
When you have extensive resources
When you don’t expect a very high response
Two general approaches to sampling are used in social science research. With probability sampling, all elements (e.g., persons, households) in the population have some opportunity of being included in the sample, and the mathematical probability that any one of them will be selected can be calculated. With nonprobability sampling, in contrast, population elements are selected on the basis of their availability (e.g., because they volunteered) or because of the researcher's personal judgment that they are representative. The consequence is that an unknown portion of the population is excluded (e.g., those who did not volunteer). One of the most common types of nonprobability sample is called a convenience sample – not because such samples are necessarily easy to recruit, but because the researcher uses whatever individuals are available rather than selecting from the entire population.
Because some members of the population have no chance of being sampled, the extent to which a convenience sample – regardless of its size – actually represents the entire population cannot be known