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Research Methodology Interview Questions
08/20/2018
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What's more, that 0. Przybylski puts it another way: That the negative impact of listening to music is 13 times larger than the effect of social media. In datasets as large as these, it's easy for weak correlational signals to emerge from the noise. There are several things to notice in the extended quote above.

First let's unpack what it means to, "explain 0. In this case, it tells you how much of the variance in depressive symptoms is explained by social media time and by elimination, it tells you what percentage is attributable to something else. We can take the square root of 0.

On what data might he be basing this claim? Illustrate your answer with two well-labelled scatterplots, one for social media and the other for potatoes.

Now add a third scatterplot, showing listening to music. Here are your choices: What statistical concepts are being applied here? The second scatterplot should be labeled with "social media use" on the x axis and "depression symptoms" on the y axis. These first two plots should show a positive slope of points with the points very spread out--to indicate the weakness of the association. The spread of the first two scatterplots should be almost the same, to represent the claim the two relationships are equal in magnitude.

Gender moderates changes the relationship between screen use and depression. Therefore, large data sets can show statistical significance for even very, very, small correlations--even correlations that are not of much practical interest.

A researcher might report a "statistically significant' correlation, but it's essential to also ask about the effect size and its practical value the potatoes argument.

That means that we can't be sure if social media is leading to the slight increase in depressive symptoms, or if people who have more depressive symptoms end up using more social media, or if there's some third variable responsible for both social media use and depressive symptoms.

As the Wired article states,. They need randomized controlled trials, to establish stronger correlations between the architecture of our interfaces and their impacts; and funding for long-term, rigorously performed research. That's why I spend so much of my time trying to do the science well," Przybylski says. Opioid addition is a major health crisis in the United States. Opioid addiction sometimes starts when a person in pain is prescribed legal opioid drugs by a physician.

Opioid prescriptions can also be sold illegally. For these reasons, opioid prescription rates are an indicator of opioid abuse in a particular region. Some public health researchers have investigated whether legalizing marijuana can reduce rates of opioid use and abuse.

Marijuana is an alternative for controlling chronic pain that, according to many experts, has a lower addiction risk. Recently, researchers published two studies, both with quasi-experimental designs, that tested whether legalized marijuana could lower the rates of opioid prescriptions. Like many quasi-experiments, the researchers took advantage of a real-world situation: ABC news covered the the research.

There were two studies with similar designs, but we'll focus on the first one:. One looked at trends in opioid prescribing under Medicaid, which covers low-income adults, between and It compared the states where [medical] marijuana laws took effect versus states without such laws Results showed that laws that let people use marijuana to treat specific medical conditions were associated with about a 6 percent lower rate [over the years studied] of opioid prescribing for pain.

That's about 39 fewer prescriptions per 1, people using Medicaid. And when states with such a law went on to also allow recreational marijuana use by adults, there was an additional drop averaging about 6 percent. What is the dependent variable? Was the independent variable independent groups or within groups? Non-equivalent control group posttest only? Non-equivalent control group pretest-posttest? Interrupted time series design?

Non-equivalent control group posttest-only design? Here's the study using Medicare Part D prescription rates , and here's the study using Medicaid prescription rates. It was independent groups states either had, or had not, legalized the drug. The dependent variable was the number of opioid prescription rates through Medicaid. Another variable, somewhat difficult to discern from the journalist's description, was year of study from to The researcher did not decide which states could legalize marijuana or not.

There were two types of states legalized and not and one main outcome variable: The prescription rate was compared over time from to , making it pretest-posttest. You could then have "States with legalization" and "States without legalization" as two different colored lines.

Presumably although this is not clear from the articles , represents a year before many of the marijuana laws took effect and data occurred after the laws had been active. As for internal validity, it's possible that states that legalize are different in systematic ways than states that do not.

For example, states that legalize marijuana are more likely to be in the North and West, have lower poverty rates, and so on.

However, the pretest-posttest design, in which they studied the "drop in opioid prescriptions over time" rather than "overall rate of opioid prescriptions" helps minimize some of these concerns. As with most quasi-experiments, causation is not a slam-dunk, because the experimenter does not have full control over the independent variable. According to several previous studies in psychological science, men with wider faces--a greater ratio of width to height like in the photo on the left, compared to the right --tend to show antisocial tendencies such as racial bias, exploitation, and even aggression.

Researchers attributed this link to exposure to testosterone during development, which, they say, causes both wider facial structure and antisocial behavior. However, a study led by Michal Kosinski has questioned this basic relationship.

Here's how the APS website describes the inspiration for the work:. Kosinski found that previous studies often had methodological shortcomings such as small sample sizes. Half of the previous studies that he identified involved fewer than 25 participants and the average sample size was These factors led Kosinski to conduct a large-scale study of face measurements and behavioral tendencies.

You might also want to review the "kindergarten height" example in this recent blog post. Now read a bit more about the "big data" methods that Kosinski employed in his research: Kosinski turned to a very large dataset collected via a Facebook app called MyPersonality.

The app comprised a collection of psychometric tests and surveys that Facebook users could take and then see how they scored — they could also volunteer their scores and Facebook profile data to be used in research projects. Do broad faces indicate antisocial tendencies? After a preliminary experiment with 1, users showed that a computer could measure width-to-height ratios with the same accuracy that humans could, Kosinski analyzed , photos from , male and female participants some users had multiple profile pictures and their measurements were averaged before analysis.

Moreover, broader-faced people did not score significantly higher on any of the traits positively related to antisocial and aggressive behavioral tendencies, including the personality facets of excitement-seeking and anger, impulsiveness, and militarism i.

Now sketch a scatterplot of the result, labelling your axes carefully. Why might this lead to a more stable estimate of the true relationship between facial broadness and personality? This is the complement to question a , above. The gifs in this blog post show the principle dynamically. P-hacking is when a researcher goes through a series of options when analyzing the data, such as eliminating outliers, adding covariates, or testing multiple dependent measures, stopping analysis only when p just crosses under the.

Therefore, when, in a body of literature, most of the p -values are just below. We cannot be sure without more investigation into the original studies, but these are the two issues raised in the APS summary of Kosinski's work. The full manuscript might report more about whether data collected with these personality measures shows that they are reliable and valid. Sleep is an essential human function and getting more sleep is associated with improved mood, cognitive performance, and physical performance.

Therefore, it might make sense that sleep would improve people's productivity and ability to earn money. That's the topic of a Freakonomics episode on the "Economics of Sleep. The section I focus on starts around minute Freakonomics' hosts interviewed a set of economists including Matthew Gibson, Jeff Shrader, Dan Hamermesh, and Jeff Biddle about their research on sleep, work hours, and income.

The economists mentioned that, in order to establish a causal link between sleep and income:. What we need is something like an experiment for sleep. Almost as though we go out in the United States and force people to sleep different amounts and then watch what the outcome is on their wages.

While it is theoretically possible to conduct such an experiment, it is practically difficult to assign people to different sleep conditions for a long enough period of time to notice an impact on their wages. So the economists took an alternative path and used quasi-experimental data.

In a creative twist, they compared wages at two ends of a single American time zone. Consider two places like Huntsville, Alabama — which is near the eastern edge of the Central Time Zone — and Amarillo, Texas, near the western edge of the Central zone. Now, what good is that to a pair of economists interested in sleep research?

It turns out that the human body, our sleep cycle responds more strongly to the sun than it does to the clock. People who live in Huntsville and experience this earlier sunset go to bed earlier.

And the people of Amarillo go to bed quite a bit later. If we plot the average bedtime for people as a function of how far east they are within a time zone, we see this very nice, clean nice straight line with earlier bedtime for people at the more eastern location. But since Huntsville and Amarillo are in the same time zone, people start work at roughly the same time, which means alarm clocks go off at roughly the same time.

That means if you go to bed earlier in Huntsville, you sleep longer. The economists didn't use only Huntsville and Amarillo--they also conducted multiple comparisons of cities around the U. Using "city of residence" as their quasi-experimental operationalization of "amount of sleep", the economists were ready to report the results for wages: So now Gibson and Shrader plugged in wage data for Huntsville vs.

Amarillo and other pairs of cities that had a similar sleep gap. We find that permanently increasing sleep by an hour per week for everybody in a city, increases the wages in that location by about 4.

If you get an extra hour per night, Gibson and Shrader discovered — here, let me quote you their paper: Non-equivalent control group posttest only, Non-equivalent control group pretest-posttest, Interrupted time series, or Non-equivalent control group interrupted time series? What do you think?

Can their study support this claim? Apply the three causal rules, especially taking note of internal validity issues that this study might have. Name two or three such threats considering Huntsville and Amarillo as an example. Now consider, how might many of these internal validity threats be reduced by conducting the same analysis over many other city pairs? What do you think about that?

East or West" and the DV is "Wages". People in cities in the Eastern portion of time zones get more sleep and have higher wages than people in the Western portions.

Temporal precedence is unclear, I think: Because the data were collected at the same time, it's not clear if the timezone came first, leading to more sleep and higher wages, or if people began to earn higher wages first, and then systematically moved Eastward. However, the second direction certainly seems less plausible than the first. As for internal validity , if we consider only the city pair of Huntsville and Amarillo, we could come up with several alternative explanations.

The two cities have different historical trajectories and different ethnic diversities; they are in two different states that have different fiscal policies and industry bases.

Perhaps Amarillo has poorer wages in general and people are losing out on sleep there because they are working more than one job. However, these internal validity threats become less of an issue when you consider multiple pairs of cities. Even though the method is fairly strong, psychologists would be unlikely to make a strong causal claim simply from quasi-experimental data like these, because the independent variable is not truly manipulated.

Nevertheless, the method and results of this quasi-experiment are certainly consistent with the argument that getting more sleep may be a factor in earning higher wages. A report in Time magazine carries the headline, " Cell phone distracted parenting can have long-term consequences: In the video accompanying the story, the narrator warns:.

Devoting more attention to your smartphones than to your children could mean that they'll have improper brain development and emotional disorders later in life. Put down this blog right now and pay attention to your kiddos! On the other hand, keep on listening, and you'll hear that the study in question was done on What are the three variables in the red quote above?

Now, read this excerpt from the Time article and decide how each of those conceptual variables was operationalized in the study: Tallie Baram, professor of pediatrics and anatomy-neurobiology at University of California, Irvine, and her colleagues used a rat model to study how good but disrupted attention from mothers can affect their newborns.

Baram placed some mothers and their pups in modified cages that did not have sufficient material for nesting or bedding. This was enough to distract the mothers into running around looking for better surroundings and end up giving their babies interrupted and unreliable attention.

Baram and her team compared the development of newborns raised in this environment to those raised in the normal cages where mothers had enough material to create a comfortable home. When the offspring grew older, the researchers tested them on how much sugar solution they ate, and how they played with their peers, two measures of how much pleasure the animals were feeling and a proxy for their emotional development. The rats raised in the modified environments consistently ate less of the sugar solution and spent less of their time playing and chasing their peers than the rats raised in the normal setting.

How was "Distracted parenting" operationalized here? To what extent is it reasonable to generalize from rat models of parenting to human parenting? The researcher is invisible and works hard not to interrupt the natural dynamics of the situation being investigated.

Use all of your senses, not just your sense of vision. Record the sounds, smells and tastes if applicable. Record your impressions and feelings. How do you feel while observing? Were you frightened, surprised, anxious, amused, excited?

Relate what you were feeling to what you were observing. Record the context of the situation: Record what you were thinking during the observation. Did the situation remind you of something similar? Had you experienced something similar.

What do you think the participants were thinking about while you were observing? Record all of your information in a journal. Use shorthand or abbreviations if necessary. Completeness of information recorded is critical to gain a complete understanding of the dynamics of the situation. Accuracy of the information recorded. Did you miss anything? Did you record it exactly as you observed it? Would someone else who had not observed the same thing be able to get a clear, correct picture of what you observed by reading your notes?

Be sure not to name people or places in your presentation of the information. You have not asked for their permission to conduct research, and so therefore they have to right to remain anonymous. Refer to the general situation, for example, a school playground, an urban mall, a farm, a family gathering, etc. Use only your written notes. Interview research usually involves the interviewer asking a series of questions which are then recorded in some manner.

Prepare your interview questions in advance, and share them with the participant s. Tape record, or videotape record the interview.

Do not be afraid to ask questions if they arise during the interview, even if you did not have them listed before the interview. After the interview, you will need to transcribe copy exactly what was said during the interview. This can be a very slow, and timing consuming process, but it is critical that you copy exactly what was said.

After you have copied out the interview, replay the interview again and compare it to your notes. Make any corrections necessary. Share the written copy of the interview with the participant to make sure that they agree with, and affirm the contents of the interview.

Completeness of information recorded is critical to gain a complete understanding of the accuracy of the interview. Did you record it in written form exactly as was said by the participant? Would someone else who had not interviewed the participant be able to get a clear, correct picture of what was discussed by reading your notes?

Be sure you have asked for their permission to be interviewed, and that they are aware of the purpose and intended audience of the interview. A case study is an intensive study of one individual. Typically, the case study may involve interviews, observation, experiments and tests.

Prepare your research questions in advance: What kinds of information do you want to know? Consider many different forms of information sources: Online websites, paper-based sources such as encyclopedias, journals, magazines and newspapers. If the case study is of a person who can be interviewed, review the following: Case studies may also include observational research, experiments and tests. Consider what other types of research are appropriate.

Completeness of information recorded is critical to gain a complete understanding of the accuracy of the case study. Have I checked every conceivable resource for information?

Because of the variety of information sources, be sure that you have reviewed all of the issues or concerns for each of the research types. Would someone else who had not case studied the participant be able to get a clear, correct picture of what was discussed by reading your report?

Be sure you have asked for their permission to be case studied, and that they are aware of the purpose and intended audience of the report. A topical research project involves the acquisition, synthesis, organization and presentation of information. Completeness of information recorded is critical to gain a complete understanding of the topic. Would someone else who had not researched the topic be able to get a clear, correct picture of what the topic was all about by reading your report?

If you have interviewed or case studied an individual connected with the topic, be sure you have asked for their permission to be studied, and that they are aware of the purpose and intended audience of the report. Experimental researchers manipulate variables, randomly assign participants to various conditions and seek to control other influences.

Conducting research using a survey involves going out and asking questions about the phenomenon of interest. What Is Q Methodology? Q Methodology is a research method used to study people's "subjectivity" -- that is, their viewpoint. Q Methodology was originally developed by William Stephenson , an Englishman trained in physics Ph.

It has been used both in clinical settings for assessing patients, as well as in research settings to examine how people think about a topic. The basic steps of the Q sorting procedure are as follows. A heterogeneous set of items called a Q sample is drawn from the concourse. A group of respondents P set is instructed to rank-order Q sort the Q sample along a standardized continuum according to a specified condition of instruction.

Participants do this according to their own likes and dislikes thus according to their own 'psychological significance'. The resulting Q sorts are submitted to correlation and factor analysis. Interpreted results are factors of 'operant subjectivity'. A study is regarded as scientific if the following three standards have been met:. Why Is Scientific Study Important? It enables us to acquire knowledge based on verifiable evidence.

What Does Double-blind Mean? When a "double-blind" procedure is used in a study, it means that neither the participants nor the researchers know which condition the participants have been assigned to. One way to do this, would be to use a double-blind study in which participants were given either normal chocolate or sugar free chocolate and neither the researchers nor the participants will be able to tell which chocolate they had been given.

Why Is This Important? The "double-blind" procedure is one of a number of general control procedures that is designed to minimise the effect of two things:. Analyse Multi-stage And Sequential Sampling? In multi-stage sampling method, sampling is carried out in two or more stages. The population is regarded as being composed of a number of second stage units and so forth.

That is, at each stage, a sampling unit is a cluster of the sampling units of the subsequent stage. First, a sample of the first stage sampling units is drawn, then from each of the selected first stage sampling unit, a sample of the second stage sampling units is drawn. The procedure continues down to the final sampling units or population elements. Appropriate random sampling method is adopted at each stage.

It is appropriate where the population is scattered over a wider geographical area and no frame or list is available for sampling. It is also useful when a survey has to be made within a limited time and cost budget. The major disadvantage is that the procedure of estimating sampling error and cost advantage is complicated. Sequential sampling is a non-probability sampling technique wherein the researcher picks a single or a group of subjects in a given time interval, conducts his study, analyses the results then picks another group of subjects if needed and so on.

This sampling technique gives the researcher limitless chances of fine tuning his research methods and gaining a vital insight into the study that he is currently pursuing. There is very little effort in the part of the researcher when performing this sampling technique.

It is not expensive, not time consuming and not workforce extensive. This sampling method is hardly representative of the entire population. Its only hope of approaching representativeness is when the researcher chose to use a very large sample size significant enough to represent a big fraction of the entire population.

Due to the aforementioned disadvantages, results from this sampling technique cannot be used to create conclusions and interpretations pertaining to the entire population. Research simply means a search for facts — answers to questions and solutions to problems.

It is a purposive investigation. It is an organized inquiry.

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· The entire research process is covered from start to finish: Divided into nine parts, the book guides readers from the initial asking of questions, through the analysis and interpretation of data, to the final report · Each question and answer provides a stand-alone explanation: Readers gain.

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Stanford Libraries' official online search tool for books, media, journals, databases, government documents and more. Answers to selected questions a) The IV is "Hours of sleep" (but you could also call it "location on the time zone: East or West") and the DV is "Wages". b) The IV is independent-groups.