scom 388 exam 2

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1
what are the 6 issues that researchers face when picking a research topic?
  • empirical concern

  • ethical concern

  • practical concern

  • is the problem significant?

  • what costs and time are involved?

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empirical concern
Can problems be investigated?
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Ethical concern
Is there potential harm to subjects?
- What happens when we lock people in a room for weeks and make them watch violent media?
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4
Practical concern
  • Can the data be analyzed?

  • Have enough practical concerns?

  • Can you get access to data? Or people?

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5
Is the problem significant?
ex: does Tv affect pets?
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6
Can results be generalized?
Do results only apply to a subset of JMU students or students at all universities?
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What costs and time are involved?
Days, years, decades?
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8
what are the steps associated with conducting a focus group?
  • define problem

  • sample selection

  • determine number of focus group

  • study mechanics

  • prepare materials

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Defining problem
  • Is a focus group a proper research method?

  • What is already known?

  • What additional info is required?

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Sample selection
6 to 12 similar people participating in a focus group BUT do not know each other.
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Determine number of focus groups
Typically want multiple groups with different characteristics depending on your topic.
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Study mechanics
  • When is it going to be held?

  • Where is it going to be held?

  • How are you going to record it?

  • Will you offer an incentive?

  • Notify participants time and place

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Prepare materials
Consent form: Participants acknowledge they are participating in research, especially when recording sessions.
Protocol/interview guide: A script for the moderator
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14
what are the types of main questions in a focus group protocol
  • opening question

  • intro question

  • transition question

  • key question

  • ending question

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Opening question
easy, factual question that serves as an ice breaker
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Intro question
General impression of the topic
- What’s your general feelings about social media? When do you use it?
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Transition questions
Guide participants toward key topics
- What are the negatives and positives of using social media relative to class work?
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Key questions
  • Questions that address the heart of the issue

  • How do you use social media to study?

  • How does it hurt job prospects?

  • How does it increase or decrease productivity?

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Ending questions
Summarize what has been said, ask for clarification
This is what you have said, correct? Anything else?
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What are common problems the moderator needs to address?

Personal bias and consistency:

  • Reinforce the opinions that are consistent with yours

  • Look for a specific answer, so you push the conversation

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21
pros and cons of conducting a case study
Pros:
· Provides lots of detail about the case/situation.
· Helps understanding of an issue.
· Good at figuring out WHY something occurred in a specific situation.
Cons:
· Lack of generalizability
· Lack of scientific objectiveness
· Lack of information accessibility
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22
what is a case study?
an up-close, in-depth, and detailed examination of a particular case
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23
What does it mean to have a conceptual fit and provide an example of what a good conceptual fit would look like.
  • You want to fit between your conceptual definition and operational definition.

  • ex: a saw a good match for the job of cutting a piece of wood

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24
In terms of measurement, what does it mean to have a valid measure?
The measure is actually measuring what you defined to measure.
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In terms of measurement, what does it mean to have a reliable measure?
Measures provide consistent results.
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Assessments of validity
  • Face Validity

  • Content Validity

  • Criterion Validity

  • Discriminant Validity

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Face Validity
The measure seems to look good on the face of it (i.e., it looks right on the surface)
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Content Validity
the measure captures the full range of meanings/dimensions of the concept (i.e., ALL aspects of the concept).
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Criterion Validity
The results of your measure correspond to the results of other related measures that are considered valid
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Discriminant Validity
The measures can discriminate between known different groups.
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31
what are the ways to test reliability?
  • Test – retest

  • Split-hal

  • Cronbach’s alpha

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Test – retest
Measure the same thing twice and see if the two tests obtain the same results
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Split-half
split the measures to two portions. Let some participants take one portion of the measures and others take the other portion. Then compare results between the two groups.
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Cronbach’s alpha
Stat that assesses whether items get similar scores
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four levels of measurement

Categorical measurement: Nominal, Ordinal

  • Data are fairly simple and are language based (e.g., gender, education level) Continuous measurement: Interval, Ratio

  • Data are more complex and have equivalent distance on scale (e.g., measures as inches, miles)

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36
What were the guidelines for creating survey questions discussed in class?
  • Be clear

  • Keep questions short

  • Avoid negatives

  • Avoid double barreled questions

  • Avoid leading questions

  • Avoid asking questions difficult to answer

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representative/probability sample
a sample from a larger group that accurately represents the characteristics of a larger population
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non-representative/non-probability sample
A member of a population does not have an equal chance of being selected
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39
Different types of non-probability samples
  • Convenience

  • volunteer

  • Snowball

  • Purposive

  • Quota

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Convenience
  • When subjects are selected based on availability to the researcher

  • Selection is generally not perfect for the purpose of research

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Volunteer
  • individuals volunteer to be included

  • Extra credit, try new product, discounts

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Snowball
  • the researcher approaches one subject, ask that subject to suggest others, and it continues

  • Useful for hard to reach subjects to understand social networks

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Purposive
  • choose certain sample for special reason

  • Subjects are selected “on purpose”

  • E.g., wine experts, victims of abuse

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Quota
  • Goal is to get the sample to look like population (e.g., 50% males, 50% females)

  • Samples from the population nonrandomly

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45
What does central tendency tell you?
The center of the data
ex: average exam scores for a class
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What are common measures of central tendency?
Mean, Median, and Mode
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What visualization can be used to report frequency?
Pie chart, bar chart, line chart, histogram
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What does dispersion tell you?

The distribution of data

  • How spread out the data are

  • How different are people’s responses?

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What are common measures of dispersion?
Range, Deviation, Variance, Standard Deviation
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What is standard deviation?
  • Square root of the variance

  • Most commonly used to measure how spread out the data set is

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What would your data look like if you had a small standard deviation vs. a large standard deviation?

Large SD

  • The values in the data set are far away from the mean, on average. In other words, the scores for people tend to be spread out. Small SD

  • The values in the data set are close to the mean of the data set, on average. In other words, the scores for people to be close together.

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52
How do inferential statistics differ from descriptive statistics?

Inferential statistics:

  • Looks at two or more variables at the same time

  • Allows us to make statistical inferences about the relationships between variables Descriptive statistics:

  • describes data

  • (e.g., mean, standard deviation) and inferential statistics allows you to make predictions (“inferences”) from that data.

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What is the null hypothesis (H0)? Why do we have the null hypothesis?
  • In inferential statistics, the null hypothesis is a default position that there is no relationship between two variables.

  • We must start with the assumption that no relationship exists and find evidence to the contrary

  • E.g., Playing violent video games does not make you more aggressive.

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What is the p-value and what does it tell us?
  • The p-value (or probability value): the probability of finding the null hypothesis is is true A smaller p-value means:

  • Less probability that the null hypothesis is true

  • Stronger evidence to support the alternative hypothesis

  • If the p-value is less than .05, you are confident enough to reject the null hypothesis (and support the alternative hypothesis)

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55
What question is correlation good at answering?

How is A related to B?

  • Correlation: examines a relationship between two variables What test do we use to test for a correlation?

  • The Pearson Correlation Coefficient​ (r) a.k.a Pearson’s r How do you tell the strength and direction of a correlation? / = positive; \ = negative Strength Rules of Thumb:

  • Less than .3 = very weak relationship

  • between .3 and .5 = weak relationship

  • between .5 and .7 = moderate relationship

  • over .7 = strong relationship

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56
What question is a t-test good at answering?
  • Is A greater than B?

  • T-Test: tests the differences of means between two variables

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57
What question is an ANOVA good at answering?
  • What are the differences between groups? (Comparing 2+ groups)

  • ANOVA = Analysis of Variance What test do we use in an ANOVA if you have more than two groups?

  • post hoc test

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58
What question is a cross-tab/chi-squared good at answering?

Is category A related to category B? Cross-tabulation

  • used to test the relationship between categorical data (i.e., nominal level measure)

  • A chi-square test is used to measure cross-ta

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59
What variables do you use in a crosstab/chi-squared test?
Row variable and column variable
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