Applied Research Methods Midterm Study Guide

Describe the role of tradition and authority as sources of secondhand knowledge.

Secondhand knowledge are things we do not question but can put us in the wrong direction. Tradition is something that has been passed down through generations and we take as true and plausible because person telling you has your best interest at heart until it no longer serves a purpose in our lives and we can dispose of the knowledge. Authority is testing how far a person’s knowledge can go. Simplifies lives, provides info we don’t question but could lead us on wrong path.

8. Define and illustrate the following error in inquiry: inaccurate observations

Inaccurate observations are the natural errors that occur when humans try to recall an observation. For example, if a room all watched the same event occur, people throughout the room will have come to different conclusions based on their proximity, background, and perspectives.

8. Define and illustrate the following error in inquiry: overgeneralization

Overgeneralization is the tendency to see patterns or trends and apply them to (every similar event) a large group when the patterns do not actually apply to the population. This can occur when a study is done on a small sample of people and the results are applied to a large population that is vastly different than the sample. similar to stereotyping

8. Define and illustrate the following error in inquiry: selective observation

Selective observation is the tendency to only find and seek out patterns that are aligned with what you are expecting and ignoring other possibilities. This can occur when researchers have a desired outcome and will skew the results to fit their outcome. Ignore alternative information, tunnel vision

8. Define and illustrate the following error in inquiry: illogical reasoning

Illogical reasoning is the tendency to jump to conclusions in research that most likely benefit us. This can be illustrated through the gamblers fallacy where people keep betting money on slot machines because they have not won and they believe they are close to winning, so they will keep playing not understanding their chances are the same each time. Using the exception to prove the rule, conclusion doesn’t make sense, not using logic explicitly

16. Differentiate independent and dependent variables by definition and example, and show how they contribute to understanding causality.

Independent variables are logical groupings of attributes that we manipulate for the research and are the influence or the cause of the dependent variable. They are usually what we are curious about seeing the effects of and causes another variable. The dependent variable represents the results or consequence of the manipulation to the independent variable. This variable is uninfluenced by the researchers and dependent solely on the happenings in the study. Ex. Age is the independent variable and math skill is dependent , the older a person gets the better they will be at math

17. Compare idiographic and nomothetic explanations.

Idiographic causal reasoning is to explain the studied behavior in as much explicit detail as possible for a single case or a small sample. It is more time consuming so it is not as common. Nomothetic casual reasoning is coming to an average generalizable broad conclusion that allows the most individuals to benefit from the research applied to a group. The answer will be less specific because of the wide applicability.

18. Compare induction and deduction as ways of developing theories.

Inductive theory is when we start with the data collection to then analyze the results to create a theory, which is more used in therapeutic situations, looking for themes or patterns in data to lead to theory which is end goal. Deductive theory starts with the theory and created a hypothesis and a research design study based on the theory. After the data has been collected we compare the results to the hypothesis and decide if it has validity.

1. List the three functions of theory for research.

Theories prevent flukes in research, ensuring something took place enough times in real life to be called a theory. They also make sense of observed patterns to suggest other possibilities, extending what we know to discover new things. Finally, they can direct research efforts by providing a starting place for research that can point toward discoveries.

2. Define paradigm.

Paradigms provide a framework for observation and understanding, providing us with a way to observe something which ultimately impacts what we see and how we understand it. This can provide us with new ways of seeing and explaining things in research.

Provide synopses for each of the following paradigms: early positivism

Early positivism- replacing older religious beliefs and resolutions with observations and knowledge

Provide synopses for each of the following paradigms: conflict

Conflict- every interaction has an element of conflict, you are either trying to dominate or trying to avoid being dominated

Provide synopses for each of the following paradigms: symbolic interactionism

Symbolic interactionism- interactions are based on reaching an understanding through language and systems, the things you do and ppl you associate with are a reflection of you

Provide synopses for each of the following paradigms: ethnomethodology

ethnomethodology- people want to predict circumstances and we dont realize the norms of society until they are broken. This paradigm looks at the reactions to rule violations.

Provide synopses for each of the following paradigms: structural functionalism

A social entity, such as an organization, can be viewed as an organism. A social system is made up of parts, each of which contributes to the functioning of the whole. This view looks for the “functions” served by the various components of society.

Provide synopses for each of the following paradigms: feminist

feminist- laws do not take into consideration women

Provide synopses for each of the following paradigms: CRT

CRT- laws do not take into consideration people of color

Provide synopses for each of the following paradigms: natural selection

natural selection/darwinism- survival of the fittest, some ppl have innate qualities that make them better than others.

6. Show the role of theory, operationalization, and observation in the traditional model of science.

Theories are interrelated statements that are intended to explain a social reality and serve as a starting point or inspiration for research in the traditional model of science. Operationalization is turning more abstract variables we are studying into measurable and observable variables for research. Observations are how we actually collect data through seeing hearing and touching.

8. Differentiate inductive from deductive reasoning by definition and example.

Inductive reasoning begins with a blank slate and develops generalizations from specific observations. This allows the data to do the majority of the work and have no preconceived notions in the analysis. An example would be assuming all flamingos are pink because all the ones I have studied are pink. Deductive reasoning is using theories to develop expectations or hypotheses about research. An example of this would be using feminist theory to explain the overrepresentation of women in the caregiving field.

4. Describe the three main criteria for nomothetic, causal relationships.

There must be a relationship or correlation between two or more variables. There also must be a time factor that shows the independent variable comes before the dependent variable. Finally, there cannot be a third variable explaining the relationship, non-spurious, genuine relationship.

7. Define and illustrate the ecological fallacy.

The ecological fallacy states that what you find out about a group you cannot apply to the individual, only to the group. Just because the average age in the class is 22, does not mean every student will be 22.

8. Define and illustrate reductionism.

Reductionism is giving too simple of an explanation for something when it is actually more complex. It is not wrong, but other factors have an influence. An example of this would be saying a certain race engages in more criminal activity than others, when in reality there are institutional and systemic factors that contribute.

11. Differentiate among the three types of longitudinal studies trend by definition and example. trend

trend - these study changes of populations over time, Ex. comparing US censuses

11. Differentiate among the three types of longitudinal studies trend by definition and example.

cohort - examining specific subpopulations as they change over time Ex. people of a certain age

11. Differentiate among the three types of longitudinal studies panel by definition and example.

panel - examining the same set of people over time Ex. studying a group of mothers over years of their childrens lives

14. Explain why attributes of a variable should be exhaustive and mutually exclusive, and give examples of each.

Attributes of a variable should be exhaustive meaning the list provided should be complete so the participant can see themselves in the responses provided. All possible responses should be included and also an other/don’t know option. For example, all gender identities should be represented in a list, not just female and male. They should also be mutually exclusive so there are no overlapping attributes so people can only identify one answer. This makes life easier for the researcher analyzing the results and the participant to answer the questions. This is important so participants don’t get frustrated and skip or sway the results. For example, if there is a question about if you are unemployed but also a question about your career.

15. Differentiate the following four levels of measurement and give an example of each:

nominal- no numerical value attached, only a naming category to describe, Ex. gender

15. Differentiate the following four levels of measurement and give an example of each:

ordinal- this measure has a rank order to them, participants can be ranked and compared by who is higher or lower on construct being studied, not how much just which side they fall to. Ex. in a race, cant tell how much faster a person was but they did get first place *********

15. Differentiate the following four levels of measurement and give an example of each:

interval - this measure has a rank order but there is an equal distance between attributes, there are set intervals between each that can be compared to others, and there is no true zero point. an example is temperature, IQ

15. Differentiate the following four levels of measurement and give an example of each:

ratio- ratio measures have all the same qualities as the last, but it has a true zero point and comparisons can be made in terms of ratios. EX. how many children do you have, a person can have zero kids, so this would make sense.

19. Define reliability and compare these strategies for improving the reliability of measures:

Reliability is how dependable the collection of data is and making sure you get the same data on multiple observations. Consistency.

19. Define reliability and compare these strategies for improving the reliability of measures:

test-retest method- this is administering the same assessment on multiple occasions, generally two weeks apart.

19. Define reliability and compare these strategies for improving the reliability of measures:

split-half method- halfing a measure and administering it half at a time to see if they are consistent, ****this is when you make more than one measurement of a social concept that are consistent and related and compare them to make sure they are consistent.

19. Define reliability and compare these strategies for improving the reliability of measures:

using established measures- every social concept has been studied and has an established measure that has already been tested so using an established measure can be much easier.

19. Define reliability and compare these strategies for improving the reliability of measures:

reliability of research workers- if you have multiple data collectors, ensure they are all using the same techniques during collection so no data is skewed or biased.

20. Define validity and compare these types of validity:

Validity is ensuring you are measuring what you say you’re measuring and that you are accurate that it is reflecting the intended concept.

20. Define validity and compare these types of validity:

face validity- this is ensuring the question or item used for measurement is related to the topic and makes sense. making sure it makes logical sense to ask that question.

20. Define validity and compare these types of validity:

construct validity- this is when you use another measure that is theoretically related to the construct of interest and make sure the relationship needs to hold true and if one doesn’t match determine which is wrong. Essentially the degree to which a measure relates to other variables as expected within a system of theoretical relationships and making sure it holds true how you would expect.

20. Define validity and compare these types of validity:

content validity- this is making sure your measure covers the range of meanings included within a concept and all the measures you would assume.

3. Differentiate index from scale by definition and example.

Indexes simply add how many questions a person said yes to or got right, they only accumulate scores assigned to individual attributes. They provide an easier summary score. An example is a political activism survey where one point is given for each action taken on a 6 item list, where the highest score would be 1 and lowest would be 6. A scale provides a summary score that is based on the pattern of how a person answers where some items are heavier or weaker degrees of the variable. An example of this would be a political activism survey that begins with asking a question from the extreme side of scale, such as if a person has ran for office, and if they answer yes then they are automatically assumed they would say yes to the rest because they have weaker degrees of the variable and the highest has already been confirmed.

11. Describe three strategies for handling missing data in index construction.

If there is only a few cases with missing questions on a long survey, a researcher can choose to exclude the couple of cases. They can also treat a lack of response as an available response. Finally, they can analyze the missing data to interpret the meaning.

13. Describe the logic and procedures of the Bogardus Social Distance scale.

This scale measures a persons willingness to interact with someone who is different than you and their comfort in the situation. This could be used by asking if someone would be comfortable having a sex offender as a close relative by marriage as a first question. If they say yes, then you can assume they would be okay with the smaller questions as well such as as a neighbor or coworker. If they say no, you must go down the scale to gauge their comfortability level.

16. Describe the logic and procedures of the Semantic differential.

The semantic differential is using the likert scale, a set structure of response options, placed between two extremes as indicators. This can be like asking about musical preference on a scale of enjoyable to unenjoyable.

17. Describe the logic and procedures of Guttman scaling.

Guttman scaling is assigning a score based on a pattern a person receives that is based on a pattern of intensity. This could be like trying to find out support for abortion and when asking about abortion for unmarried people, if they say yes then we can assume they will say yes to the rest.

1. Define sampling.

Sampling is when we select a group from a population of interest so we can study and observe a certain phenomenon on them.

3. Describe and illustrate each of the following types of nonprobability sampling:

reliance on available subject sampling - sample of convenience, This is when we use the test subjects that are easily available to us and is only used if other less risky methods aren’t possible. The generated samples will not have proper representation of the actual population due to bias in availability. An example would be a researcher surveying the first 100 people they came into contact with in a city.

3. Describe and illustrate each of the following types of nonprobability sampling:

purposive (judgmental) sampling - This sampling is when the researcher has knowledge of the population, its elements or the purpose of the study and lets these guide their sample selection. This is typically used when research is interested in irregular cases. An example of this would be studying a specific class of students that are using a unique grading system to see how they perform with the new system.

3. Describe and illustrate each of the following types of nonprobability sampling:

quota sampling - This sampling method begins with a table of the population and people are grouped based on common characteristics for data to be collected on. Each group makes up a percentage of the population so the whole is equivalent to the total population. An example of this would be sending out a survey to a sample where the researcher seeks out 50% female participants and 50% male participants. Using a matrix that identifies characteristics of a population to make sure you meet necessary proportions

3. Describe and illustrate each of the following types of nonprobability sampling:

snowball sampling - This is when a researcher locates a few people that fit the population of interest and ask the participants to recruit more people from the population for the study. This is typical when interested in a population that is not easily accessible. An example of this would be reaching out to a person with a rare disease and seeing if they know of any other people with the same condition. refer a friend technique

4. Describe the role of the informants in nonprobability sampling and provide advice on how to select them. *

Informants are people who are knowledgeable about the social phenomenon of interest and will share their advice and experience with researchers. It is vital to ensure informants are properly knowledgeable about your specific interest so the results aren’t skewed. Keep one eye open about informants because the fact that they want to talk to you makes it atypical bc typically people arent willing to share information with outsiders

6. List two advantages of probability sampling over nonprobability sampling.

Probability sampling allows us to control and estimate the amount of sampling error we are expected to find in our results. It also permits us to avoid the biases of researchers when sampling to results are accurate and representative.

10. Define sampling frame and restate the cautions regarding making generalizations from sampling frames to populations.

Sampling frames are lists of all the units that make up a population of interest from which a sample is selected. When making generalizations from a sampling frame to populations, it is important to make sure you only generalize back to a group that was similar to your selected sample. You also need to make sure all the elements have equal representation and each person has an equal chance of being selected to be generalized back.

11. Describe simple random sampling and list a reason why it is seldom used.

Simple random sampling is basically when you assign a list of people a number and use a random number generator to select your sample from the list. It is only good for very simple sampling frames and not the most accurate without a random number generator.