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- Areas of interest (most important consideration) - Knowledge subject area - Relevance to profession - Availability of data - Ethical issues |
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4 P's of a Research Problem |
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- People - Problems - Programs - Phenomena |
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Research Problem (step 1) |
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identify a broad area of interest |
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Research Problem (step 2) |
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dissect the broad area into subareas |
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Research Problem (step 3) |
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select the one that interests you most |
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Research Problem (step 4) |
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What brings clarity, specificity, and focus to a research problem? |
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A tentative assumption that the validity is not known |
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Written in such a manner that it can be proven correct, incorrect or partial correct |
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Phase 1 – Formulate assumption Phase 2 – Collect data Phase 3 – Analyze data and draw conclusion (proved hypothesis true or false) |
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Hypothesis Characteristics |
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- Simple, specific and conceptually clear - Capable of verification - Related to an existing body of knowledge - Measurable |
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- Find the answers to research questions - To prove or disprove the hypothesis - Find answers to the research problem |
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- Formulate 3 questions - Formulate hypothesis - Define the purpose of the research |
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Components of a Literature Review |
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- Define the Research Problem - Conceptualizing Research - Review Literature |
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Functions of a Literature Review |
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- Provide theoretical background for your study - Establish links between what is proposed and what has been studied - Refines research methodology - Contribution to the existing body of knowledge in profession - Contextualize findings - Clarifies and focus research - Broadens knowledge base of subject |
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Review Bibliography of Authors |
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- Knowledgeable in the area of writing - Peer reviewed, less than 3 years old - Equal or greater level to the target audience that article is being published - Prior publishing |
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Literature Review Procedure |
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- Start with broad area of interest - Keep list of words used in search engines - Form a rough outline of the main points that are going to cover (helps focus search) - Ensure the resources are reputable |
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An image, perception, or concept that is capable of measurement/capable of different values |
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gender, age, income, height, weight |
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mental images or perceptions who’s meanings vary markedly, cannot be measured |
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effectiveness, satisfaction, high achiever, rich, self-esteem, excellence |
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- Independent variables - Dependent variables - Extraneous variables - Confounding variables |
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responsible for bringing about change |
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may increase or decrease the magnitude of the relationship between the independent and dependent variable |
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Example of the relationship b/w Variables |
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- Independent variable = smoking (cause) - Dependent Variable = cancer (effect) - Extraneous Variable = duration of smoking |
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Relationship between independent and dependent variable cannot be established |
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the independent variable will have the assumed effect only in the presence of the confounding variable |
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variables that can be changed or controlled (ex.# of cigarettes smoked) |
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variables that cannot be changed (ex. age of patient, education level, income level, race of patient) |
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can only have one value (ex. water) |
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only can be divided into two categories (ex. yes/no, pass/fail) |
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can be divided into more than two categories (healthcare providers - MD, PA, DO, NP) |
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can take on any value in the scale in which they are measure Ex. weight(lbs or kgs), age(years, months, days) |
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Designed to study a phenomenon, situation, problem or issue in a cross section at one time |
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One interaction with participants |
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- Measures the change in a situation, issue, problem, phenomenon - Collect data, intervention, collect second set of data |
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Has two interactions with participants |
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- Determine patterns of change over time - Collect data over a specific set of time at set intervals |
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Three or more interventions with participants |
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- Investigates phenomenon, issues, situations, problems that have happened in the past to try to make predictions about the future |
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- Based on data available from that time - Based on participant recall of events |
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Likely prevalence of a phenomenon, situation, problem, outcome in the future |
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In experimental studies, the group of participants that do not receive intervention |
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Different groups receive different interventions and the results are compared |
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The group that receives a treatment that is ineffective |
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Based on the existence of a common character (year of birth, marriage, job description) |
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the participants do not know if they are getting the intervention or the placebo |
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researcher and participants do not know who’s getting the intervention or the placebo = eliminates bias |
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Methods of Data Collection (primary source) |
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- Observation - Interview - Survey/Questionnaire |
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Methods of Data Collection (secondary collection) |
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Data collection (observation) |
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data is collected by watching and listening to interaction taking place |
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researcher participates in the activities of the groups being observed with/without their knowledge of the observation process |
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Non-participant Observation |
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researcher does not get involved with the activity, but just watches and listens |
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Non-participant Observation |
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Problems with Observation |
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- Individual/group behaviors change if they are aware that they are being observed (Hawthorne Effect) - Observer bias - Interpretations drawn are going to vary between observers - Incomplete observation |
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Individual/group behaviors change if they are aware that they are being observed |
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Conditions of Observation |
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A) Natural – under natural conditions B) Controlled – introduce a stimulation and watching the response |
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Recording of observation (narrative) |
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researcher records interactions in their own words as soon after the event as possible |
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Recording of observation (Scales) |
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at the time of the interaction, participants are rated. - Three directional = positive, negative and neutral |
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Recording of Observation (mechanical device) |
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- video/audio to be transcribed at a later date. - Disadvantage –people act differently when video taped |
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- Structured (setting, content/questions, session) - Unstructured (setting, content/questions, session) - Group setting - Individual – one on one |
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- More appropriate for complex situations - Useful for collecting in-depth information - Information can be supplemented - Questions can be explained - Wider application – children, handicapped, elderly, illiterate |
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- Time consuming - Expensive - Quality of data dependent on interaction - Dependent on interviewer skills - Bias – researcher/interviewer |
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Data Collection (survey/questionnaire) |
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- Written list of questions - Answered by participant - Returned to researcher |
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How are surveys/questionnaires administered? |
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- Mailed - Collective administration – end of a course/conference - Public Place |
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Components of a Cover Letter |
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- Introduce you & institution - Explain main objective (2 or 3 sentences) - Explain relevance of the study - General instructions |
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Components of a Cover Letter |
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- Participation in study is voluntary - Assure respondent anonymity - Provide contact information for ?S - Return address and deadlines - Thank them for participating in study |
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Survey/Questionnaire Advantages |
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- Less expensive - Greater anonymity |
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Survey/Questionnaire Disadvantages |
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- Limited (population read/write, excludes very young, very old, handicapped, & illiterate) - Response rate is low (20-30%) - Self – selecting bias (not everyone will return the survey) |
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Survey/Questionnaire Disadvantages |
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- Decreased opportunity to clarify questions - No spontaneous response (time to reflect before response) - Questions can influence the answer of other questions - Respondent can consult others before replying |
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- Use simple everyday language - Do not use ambiguous terms - Do not ask double- barreled questions (How often and how much time do you spend seeing a doctor/PA) - Do not use leading questions (Health care is getting more expensive, isn’t it) - Do not ask questions based on presumptions (How many beers do you drink in a day) |
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Data Collection (secondary sources) |
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- Gov’t publications - Earlier Research - Personal Records - Mass media |
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Secondary Data Sources Disadvantages |
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- Validity and reliability - Personal bias - Availability of data - Format = data maybe recorded in a different format than what you were going to discuss |
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instrument (data collection method) measures what it is designed to measure - always measures accurately - Ex: place an object on one scale and weighs same on another scale |
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- Face and context validity - Concurrent and predictive validity - Construct validity |
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An instrument measures what it is supposed to based on the logical link between the questions and the objectives |
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questions cover the full range of issues and attitudes being measured |
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the degree to which the an instrument can forecast the outcome |
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how well an instrument compares with a second instrument concurrently being done |
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Based on statistical procedure the validity of an instrument is established |
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The tool/instrument is constant, stable and predictable - Example: scale is always 5 lbs heavier |
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Factors that affect reliability |
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- Wording of the questions - The physical setting - Respondent’s mood - The nature of the interaction/interview situation - Regression effect of an instrument (2nd time will get different answers) |
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Methods to determine reliability |
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- Test/Re-Test - Parallel forms of the same test |
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Attitudinal Scales (Likert scale) |
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- Finds out the degree that the respondent agrees/disagrees - Easiest to construct (open ended/closed ended questions) - Each question has the same weight |
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Attitudinal Scale (thurstone) |
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- A panel of ‘judges’ assigns a weight to each of the questions - Difficult to construct - Weakness = judges and respondents attitudes may be different |
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- Cause-effect approach - STRUCTURED AND RIGID - Proves or disproves a hypothesis - Explains prevalence, incidence and nature of the issues - More analytical - Greater sample size (>30 to be significant) |
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hypothesis is formed first |
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- Explores experiences, meanings, perceptions and feelings - Fewer cases/respondents - Data is based on subject responses and narratives - Data is more descriptive - Unstructured and flexible |
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Hypothesis is usually developed during/after data collection |
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combinations of Quantitative and Qualitative research |
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Quasi-experimental Design |
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Usually used when it’s unethical to exclude a portion of the study group from the intervention |
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Quasi-experimental Design |
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Results of a previous group not exposed to the intervention is compared to the result of the entire current group after being exposed to the intervention |
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A statistical technique summarizing and reviewing previous quantitative research data |
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- Evaluates the relative impact of independent variables - Evaluates the strength of relationship between variables |
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the group on which the research is to be conducted |
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when it is not possible to conduct research on the entire study population, a portion of the group selected |
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an analysis of the data collected from the sample group |
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applying the outcomes of the sample group towards the study population |
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Sample Group Disadvantages |
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- sample groups compromise the accuracy of your findings - data is only estimates and predictions |
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saves time, money and human resources |
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the difference between the Population Mean (PM) and the Sample Statistics (SS) |
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in qualitative research when no new data is being collected from interviews or observation |
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Study Population can be denoted by |
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sample group can be denoted by |
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Principles of Sampling (#1) |
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difference between sample statistics and the true population mean. |
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Principles of Sampling (#2) |
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The greater the sample size, the more accurate the estimates (sampling statistics) will be when compared to the true population mean. |
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Principles of Sampling (#3) |
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the greater the difference in the variables under study in a population, the greater the difference between the sample statistics and the true population mean. |
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- Random/probability sampling design - Non-random/non-probability sampling design - "Mixed" sampling design |
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Each element in the population has an equal and independent chance of being selected for the sample group |
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3 Types of Random Sampling |
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- Simple random sampling - Stratified random sampling - Cluster sampling |
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Examples of simple random sampling |
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- Fishbowl - Computer program |
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Disadvantage of Simple Random Sampling |
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may not reflect the true population |
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Stratified Random Sampling |
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Variables are entered for selection process |
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Large numbers of population can be divided into groups (Ex.city, counties, or states) |
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Types of Non-random/non-probability Sampling |
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- Quota sampling - Accidental sampling - Judgmental or purposive sampling - Snowball sampling |
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when a specific characteristic is desired for the research |
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based on convenience in accessing the sampling population |
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Judgmental or Purposive Sampling |
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gather information only from respondents that have “the best information on the subject” in the judgment of the researcher |
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- selecting sample using networks. - Each respondent suggest 3 more people to interview (biased sampling, may be good to know who has knowledge about topic) |
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Uses both random and non-random sampling |
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set intervals for selecting a population |
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processes qualitative & quantitative data |
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- Give a respondent number to each survey that you received - Number the questions on the survey - Develop mutually exclusive categories (non overlapping categories) may be same as the variables |
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link response to the code sheet |
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used for qualitative type questions |
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Framework for Analysis of Data |
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- Decide which variables to analyze - Develop main themes - Cross-tabulate the data - Which variables combined form a major concept - Analyze the data |
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most common way to present data |
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- Title: Table # - Stub (heading for the y-axis) - Column headings (labels x-axis) - Body (data) - Supplementary notes/footnotes |
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- Two dimensional - series of rectangles w/o space between them to represent data |
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used to display categories of data with spaces between them |
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Graphs (Stacked Bar Chart) |
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shows 2 or more variables stacked on top of each other |
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Particular bar totals 100% |
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Graph (Frequency polygon) |
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joins the midpoints of each rectangle at a height commensurate with the frequency of that interval |
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- represents data in a 360 degree circle – represents 100% to the total |
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display data related to a specific time |
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Best way to show how one variable changes in relationships to a change in another variable |
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- Theoretical framework of the study - Conceptual framework of the study - Research questions - Hypothesis to be tested |
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- Study design - Setting of your study - Research instruments planning to use - Sample design & sample size |
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- Ethical Issues & how to deal with them - Data processing procedures - Proposed reports - Problems & limitations of the study - Time frame & work schedule |
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