Managing Data and Survey Methods Chapter II Data Collection ● It is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. Data Collection There are 5 common data collection methods: ● ● ● ● ● Closed-ended surveys and quizzes Open-ended surveys and questionnaires 1-on-1 interviews Focus groups Direct observation Data Integrity Issues The main reason for maintaining data integrity is to support the observation of errors in the data collection process. Those errors may be made intentionally (deliberate falsification) or nonintentionally (random or systematic errors). Data Integrity There are two approaches that may protect data integrity and secure scientific validity of study results invented by Craddick, Rhodes, Redican, Rukenbrod and Laws in 2003: ● Quality Assurance – all actions carried out before data collection ● Quality Control – all actions carried out during and after data collection Data Integrity Quality Assurance ● Its main focus is prevention which is primarily a costeffective activity to protect the integrity of data collection. Standardization of protocol best demonstrates this costeffective activity, which is developed in a comprehensive and detained procedures manual for data collection. Such failures when quality assurance is compromised: ● Uncertainty of timing, methods and identification of the responsible person ● Partial listing of items needed to be collected ● Vague description of data collection instruments instead of rigorous step-by-step instructions on administering tests ● Failure to recognize exact content and strategies for training and retraining staff members responsible for data collection ● Unclear instructions for using, making adjustments tom and calibrating data collection equipment ● No predetermined mechanism to document changes in procedures that occur during the investigation Data Integrity Quality Control ● It is also responsible for the identification of actions necessary for correcting faulty data collection practices and also minimizing such future occurrences. A team is more likely to not realize the necessity to perform these actions if their procedures are written vaguely and are not based on feedback or education. Data collection problem that necessitate prompt action: ● ● ● ● ● Systematic errors Violation of protocol Fraud or scientific misconduct Errors in individual data items Individual staff or site performance problems Types of sources Researchers may use these to collect data or obtain information for their research: ● Publication source ● Internet source ● Census ● Samples Each of these sources has its advantages and disadvantages, and researches must carefully consider the quality, relevance and reliability of the data or the information obtained from these sources. Sources Publication Source A publication source is a written material, such as a book, journal article, newspaper, or magazine that contains information in a particular topic. Researchers may use publication sources to obtain background information review the literature or gather data for their research. Sources Publication Source ● Volume – typically refers to a complete set of issues published during a particular year. ● Issue – covering a different set of research articles. Ex: A scientific journal might publish four issuer per year, with each issue covering different set of research articles. The entire set of four issues published in a given year would comprise one volume of the journal. Sources Internet Source Online or internet research is a general term which refers to any electronically-retrieved data. As a general rule, they can be divided into 3 tiers depending on their reliability: ● Top-tier sources ● Mid-tier sources ● Bottom-tier sources Sources Internet Source Top-tier sources – are those with the most reliable information. Sources in this category include professional, scholarly and academic-peer reviewed journals or sites. Examples are: ● Journal of the American Medical Association ● American Journal of Psychology ● Journal of Wildlife Management Sources Internet Source Mid-tier sources – are those with credibility is likely to be high, but which may or may not be formally peer-reviewed. This means that you as a writer as responsible for judging the reliability of the information contained in these sources. Examples are: ● Government Documents in government sites ● Wikis Sources Internet Source Bottom-tier sources – are those where information is likely to be inaccurate, inadequately researched or strongly biased. Examples are: ● Homemade Websites ● Blogs ● Facebook posts, Twitter and other Social Media sites Sources Census Census – procedure of systematically calculating, acquiring and recording information about the members of a given population. This term is used mostly in connection with national population and housing censuses. Sources Samples Sample – a set of individuals or objects collected or selected from a statistical population by a defined procedure. The element of a sample are known as sample points, sampling units or observations. Sources Samples Complete Sample – a set of objects from a parent population that includes all such objects that satisfy a set of well-defined selection criteria. Sources Samples Unbiased Sample – a set of objects from a complete sample, using a selection process that does not depend on the properties of the objects. Sampling Techniques A sampling technique is a method used to select a subset of individuals or units from a larger population for study. Sampling is an important step in research as it helps to ensure that the sample is representative of the population and that the findings of the study can be generalized to the population. Several sampling techniques: ● Probability sampling ● Non-probability sampling Sampling technique Probability Sampling Probability sampling – it involves random selection of individuals or units from the population, so that each member of the population has an equal chance of being included in the sample. Sampling technique Probability Sampling: Simple Random Sampling Simple random sampling – each member of the population has an equal chance of being selected for the sample. A simple random sample can be obtained by assigning each member of the population a unique number and using a random number generator to select the desired number of individuals. Sampling technique Probability Sampling: Simple Random Sampling Ex: Suppose a researcher wants to study the attitudes of college students towards online learning. They could obtain a list of all college students at a particular institution and randomly select 100 students from that list to participate in the study. Sampling technique Probability Sampling: Systematic Sampling In Systematic Sampling, the researcher selects every nth member of the population to be included in the sample. Sampling technique Probability Sampling: Systematic Sampling Ex: Suppose a researcher wants to study the eating habits of customers at a fast-food restaurant. They could select every 10th customer who enters the restaurant during specific time frame to participate in the study. Sampling technique Probability Sampling: Stratified Sampling In Stratified Sampling, the population is divided into strata or subgroups based on specific characteristics, and a random sample is taken from each stratum. Sampling technique Probability Sampling: Stratified Sampling Ex: Suppose a researcher wants to study the voting behavior of residents in a particular city. They could divide the population into strata based on age and then randomly select a sample of voters from each age group to participate in the study. Sampling technique Probability Sampling: Cluster Sampling In Cluster Sampling, the population is divided into clusters, and a random sample of clusters is selected for the study. All individual within the selected clusters are included in the sample. Sampling technique Probability Sampling: Cluster Sampling Ex: Suppose a researcher wants to study the academic performance of students in a large school district. Rather than selecting individual students, they could select the entire schools as the clusters. They could randomly select a sample of schools from the district and then include all students in those schools in the study. Sampling technique Non-Probability Sampling Non-Probability sampling – this type of sampling relies on the judgment of the researcher or other non-random factors to select participants. Sampling technique Non-Probability Sampling: Convenience Sampling In Convenience Sampling, the researcher selects individuals who are easily accessible or convenient to study. This sampling technique is often used when the researcher has limited time, resources, or access to the population of interest. Sampling technique Non-Probability Sampling: Convenience Sampling Ex: Suppose a researcher wants to study the opinions of people in a particular city on a new transportation policy. They could select individuals who happen to be passing by a particular street corner and ask them to complete a survey. Sampling technique Non-Probability Sampling: Purposive Sampling In Purposive Sampling, the researcher selects individuals based on specific characteristics or qualities that are of interest to the study. This sampling technique is often used when the researcher is interested in a specific subgroup of the population. Sampling technique Non-Probability Sampling: Purposive Sampling Ex: Suppose a researcher wants to study the experiences of survivors of a particular type of cancer. They could recruit participants who have been diagnosed with that type of cancer through a support group or a cancer clinic. Sampling technique Non-Probability Sampling: Snowball Sampling In Snowball Sampling, the researcher starts with a small group of individuals who meet certain criteria, then asks them to refer to others who also meet those criteria. This sampling technique is often used when the population of interest is difficult to identify or access. Sampling technique Non-Probability Sampling: Snowball Sampling Ex: Suppose a researcher wants to study the experiences of individuals who experienced workplace discrimination. They could recruit a small group of individuals who have experienced discrimination and ask them to refer others who have had similar experiences. Sampling technique Non-Probability Sampling: Quota Sampling In Quota Sampling, the researcher selects individuals based on predetermined quotas for certain characteristics or qualities. This sampling technique is often used when the researcher wants to ensure that the sample is representative of the population with respect to certain variables. Sampling technique Non-Probability Sampling: Quota Sampling Ex: Suppose a researcher wants to study the preferences of customers at a restaurant. They could set quotas for different age groups, genders, and income levels, and then select individual who meet those quotas. Survey & Survey Design Survey – a research method used to collect information from a group of people, or a sample, in order to gain insights into their thoughts, opinions, behaviors, or characteristics. Surveys can be conducted using a variety of methods, including online, in-person, by mail, or by phone. Survey Design - the process of creating and planning the structure and content of a survey. How to design a good survey? Step 1: Define the survey objectives Start by clearly defining the objectives of the survey. What do you want to achieve with the survey? What questions do you want to answer? This will help you to determine the scope of the survey and the types of questions you need to ask. How to design a good survey? Step 2: Identify the target population Determine who you want to survey. This will help you to create questions that are relevant to the target population and ensure that you collect data from the right people. How to design a good survey? Step 3: Determine the survey method Decide whether you will conduct the survey online, in-person, by phone, or by mail. Each method has its own advantages and disadvantages, so choose the one that is best suited to your target population and survey objectives. How to design a good survey? Step 4: Choose the survey questions Create a list of questions that will help you to achieve your survey objectives. Make sure the questions are clear, concise, and relevant. You can use close-ended questions or open-ended questions. How to design a good survey? Step 4: Choose the survey questions Create a list of questions that will help you to achieve your survey objectives. Make sure the questions are clear, concise, and relevant. You can use close-ended questions or open-ended questions. How to design a good survey? Step 5: Use appropriate question types Choose the appropriate question types for the survey. For example, multiple-choice questions are useful for gathering quantitative data, while open-ended questions are better for gathering qualitative data. How to design a good survey? Step 6: Pretest the survey Test your survey with a small group of people before administering it to your target population. This will help you to identify any problems with the survey and make any necessary changes before distributing it to a larger group. How to design a good survey? Step 7: Design the survey layout Design the survey layout in a way that is visually appealing and easy to follow. Use clear headings and instructions to guide participants through the survey. How to design a good survey? Step 8: Ensure confidentiality and anonymity Ensure that the survey responses are confidential and anonymous. This will help to ensure that participants feel comfortable answering the survey questions honestly. How to design a good survey? Step 9: Test the survey Test the survey thoroughly to ensure that it is working as intended. Make sure that the survey is accessible and easy to use for all participants. How to design a good survey? Step 10: Administer the survey Once you have finalized the survey questions and design, administer the survey to your target population. Make sure to follow ethical guidelines for research, such as obtaining informed consent and protecting the confidentiality of participants. Questionnaire Questionnaire - is a research tool that consists of a set of pre-designed questions used to gather data from a specific population or sample. It can be used in various fields, including social sciences, marketing, and healthcare, to collect information about attitudes, opinions, beliefs, behaviors, or demographics. Several types of Questionnaires ● Structured questionnaires: These questionnaires have a fixed set of questions that are asked in a specific order. The responses are usually multiple-choice or Likert scales. ● Unstructured questionnaires: These questionnaires have open-ended questions, allowing respondents to express their opinions and ideas in their own words. ● Semi-structured questionnaires: These questionnaires combine both structured and unstructured questions. They have a set of core questions, but the respondent can provide additional information in their own words. Several types of Questionnaires ● Diagnostic questionnaires: These questionnaires are designed to diagnose specific conditions or problems, such as mental health disorders or learning disabilities. ● Attitudinal questionnaires: These questionnaires measure attitudes or opinions towards a particular topic, such as political beliefs or customer satisfaction. ● Behavioral questionnaires: These questionnaires measure behaviors, such as eating habits or exercise routines. ● Demographic questionnaires: These questionnaires gather basic demographic information about respondents, such as age, gender, and income. Several types of Questionnaires ● Customer feedback questionnaires: These questionnaires are used to gather feedback from customers about products or services. ● Employee satisfaction questionnaires: These questionnaires are used to gather feedback from employees about their job satisfaction and work environment. ● Exit questionnaires: These questionnaires are used to gather feedback from individuals who are leaving an organization or program. Steps Preceding a Questionnaire Design: ● Identify research objectives: It is important to clearly define the research objectives and the information that is needed to achieve these objectives. This helps to ensure that the questionnaire is focused and relevant. ● Define the target population: The target population should be clearly defined, including demographic characteristics and other relevant information. This helps to ensure that the questionnaire is tailored to the needs of the target population. Steps Preceding a Questionnaire Design: ● Choose a survey method: The survey method should be chosen based on the target population, research objectives, and budget. Common survey methods include online surveys, paper surveys, telephone surveys, and face-to-face interviews. ● Conduct a literature review: A literature review should be conducted to identify any existing questionnaires that may be relevant to the research objectives. This helps to ensure that the questionnaire is based on established research and avoids duplication. Steps Preceding a Questionnaire Design: ● Determine the questionnaire structure: The structure of the questionnaire should be determined, including the types of questions that will be used, the order of the questions, and the response options. ● Develop draft questions: Draft questions should be developed based on the research objectives and the target population. The questions should be clear, concise, and unbiased. ● Pretest the questionnaire: The questionnaire should be pretested with a small sample of the target population to identify any potential problems or issues. This helps to ensure that the questionnaire is valid and reliable. Questionnaires ● The purpose of a questionnaire is to gather standardized and structured data that can be analyzed and used to draw conclusions or insights about the population or sample being studied. It can also help researchers to identify patterns, trends, and correlations between variables of interest. ● By following the steps of a good questionnaire design, researchers can develop a questionnaire that is effective, relevant, and valid for the research objectives and target population.
