New Semester
Started
Get
50% OFF
Study Help!
--h --m --s
Claim Now
Question Answers
Textbooks
Find textbooks, questions and answers
Oops, something went wrong!
Change your search query and then try again
S
Books
FREE
Study Help
Expert Questions
Accounting
General Management
Mathematics
Finance
Organizational Behaviour
Law
Physics
Operating System
Management Leadership
Sociology
Programming
Marketing
Database
Computer Network
Economics
Textbooks Solutions
Accounting
Managerial Accounting
Management Leadership
Cost Accounting
Statistics
Business Law
Corporate Finance
Finance
Economics
Auditing
Tutors
Online Tutors
Find a Tutor
Hire a Tutor
Become a Tutor
AI Tutor
AI Study Planner
NEW
Sell Books
Search
Search
Sign In
Register
study help
business
communication research
Communication Research Asking Questions Finding Answers 4th Edition Joann Keyton - Solutions
7. Closed questions are complete with standardized response sets; respondents choose from the responses provided by the researcher.
6. Open questions allow the respondent to use his or her own words in responding to a question or statement.
5. Recall cues, or stimulus statements, are needed to direct or restrict participants' responses.
4. Existing and established questionnaires can be used in some instances; other- wise, the researcher has to develop the questionnaire.
3. Research questions or hypotheses drive the survey or questionnaire design.
phone.
2. Often self-administered, surveys can be dis- tributed in written format through the mail, the Web, or e-mail, or interviewers can ask questions face-to-face or over the
1. Surveys and questionnaires are the most common quantitative method used in com- munication research.
2. Statistical analysis and reporting of the data is desirable or necessary.
1. There is agreement on what the response set should be.
4. You are willing to analyze the text of the responses.
3. The set of response choices is unknown.
2. Respondents are willing and can answer the question in their own words.
1. Respondents' own words are important and you want to be able to quote what respon- dents say.
10. Present the data to others in an appropriate fashion.
9. Draw conclusions that do not overstate the limitations of your data or sample.
8. Analyze the data completely and appropriately.
7. Collect the data in an honest and ethical manner.
6. Pretest the method of data collection.
5. Design an uncluttered and easy to read survey.
4. Use open and closed questions appropriately.
3. Select existing or develop appropriate questionnaire items and response sets.
2. Select the survey format (self-report, face- to-face, phone, or online) that will best serve the purpose of the survey.
1. Design a survey or questionnaire to answer a research question or test a hypothesis.
14. All research designs can suffer from bias from researcher effects or procedural inconsistencies.
13. Online survey software can be used effectively, especially when a condition or manipulation is dependent on a participant viewing a particular text, audio, or video stimuli.
12. Communication researchers often use descriptive designs when communication phenomena do not lend themselves to ex- perimental or quasi-experimental designs.
11. Descriptive designs are those studies that do not use random assignment of partici- pants or researcher manipulation of the independent variable; as a result of lacking these controls, these research designs can- not demonstrate causation.
10. Field experiments are a form of quasi- experimental research design conducted in a naturalistic setting.
9. In quasi-experiments, the researcher uses the natural variation that exists on the inde- pendent variable to assign participants to treatment and control conditions.
8. The time between the multiple measure- ments of the dependent variable in a longitudinal design is based on the commu- nication phenomena under study and the theoretical foundation of the study.
7. In the factorial design, treatment groups are based on two or more independent vari- ables, with random assignment occurring on one of the variables.
6. In the pretest-posttest design, only individ- uals in the treatment group are exposed to the stimulus; the dependent variable is mea- sured for all participants prior to and after the treatment group receives the stimulus.
5. In the posttest only design, the dependent variable is measured only once-after participants are exposed to the stimulus.
4. Manipulation checks should be conducted to ensure that participants perceived variation in the independent variable as the researcher intended.
3. In an experiment, the researcher controls the manipulation of the independent vari- able by randomly assigning participants to treatment or control groups; this ensures that the treatment and control groups are equivalent before any treatment is applied or withheld.
2. Experimental research is used to estab- lish cause-effect relationships between or among variables, and is most often con- ducted in a laboratory.
1. There are three categories of quantitative research design: experimental forms, quasi- experimental forms, and descriptive forms.
10. Develop a research protocol to limit researcher effects and procedural bias when conducting research studies.
9. Consider the appropriateness of using online survey software.
8. Appropriately interpret findings from descriptive research designs.
7. Interpret findings from experimental and quasi-experimental designs with respect to cause-effect relationships.
6. Conduct manipulation checks of independent variables.
5. Manipulate independent variables according to their theoretical foundation.
4. Facilitate appropriate random assignment of participants to treatment and control groups.
3. Explain the benefits of experimental forms over quasi-experimental and descriptive forms.
2. Understand the strengths and limitations of each design form as it relates to research findings, and argue for your design choices.
1. Select and develop the appropriate research design for your hypotheses or research questions.
12. Sample size is estimated from the size of the population and the level of error a researcher is willing to tolerate.
11. Types of nonprobability sampling include convenience, volunteer, inclusion and exclu- sion, snowball, networking, purposive, and quota samples.
sampling technique will result in an ad- equate and appropriate sample.
10. Nonprobability sampling weakens the rep- resentativeness of a sample to the popula- tion because it does not rely on random sampling; however, it is used when no other
9. Cluster sampling is used when all members of elements of a population cannot be identi- fied and occurs in two stages: (1) the popula- tion is identified by its groups, and (2) then random sampling occurs within groups.
8. A stratified random sample first groups members according to categories of interest before random techniques are used.
7. In systematic sampling, every nth, for ex- ample every 14th, element is selected for the sample.
6. In a simple random sample, every person or element has an equal chance of being selected for a study.
5. Probability sampling ensures that the se- lected sample is sufficiently representative of the population because every person or element has an equal chance of being selected.
4. Sampling error is the degree to which a sam- ple differs from population characteristics.
3. Generalizability is the extent to which conclusions drawn from a sample can be extended to a population.
2. A sample, or subset, is selected from the population through probability or nonprob- ability sampling.
1. A population is all units-people or things-possessing the attributes or charac- teristics that interest the researcher.
6. Choose an adequate sample size.
5. Use nonprobability procedures to produce an appropriate sample.
4. Use probability sampling procedures to produce a random sample.
3. Argue for how results from a sample are generalizable to its population.
2. Identify the population and sampling frame to select an appropriate sample.
1. Describe the distinctions among population, sampling frame, and sample.
20. Regardless of how data are collected, they must be collected and reported accurately, ethically, and responsibly.
19. Validity and reliability are threatened by the choices researchers make about how they collect data, and whom or what they choose as their sample, as well as alternative expla- nations that are plausible.
18. Measurement of data must be both valid and reliable.
17. Test-retest reliability is achieved when measurements at two different times remain stable.
16. Internal reliability is achieved when mul- tiple items purportedly measuring the same variable are highly related.
15. Reliability is the degree to which measure- ment is dependable or consistent; it is expressed as a matter of degree.
14. Construct validity exists when measure- ment reflects its theoretical foundations.
13. Criterion-related validity exists when one measurement can be linked to some other external measurement.
12. Content validity exists when the measure- ment reflects all possible aspects of the construct of interest.
11. Face validity exists when the measurement reflects what we want it to.
10. Data are valid to the extent that they measure what you want them to measure.
9. Issues of validity and reliability are associ- ated with all types of measurement.
8. Ratio data are the most sophisticated data type; they have the characteristics of inter- val data and a true zero.
7. Interval data are more sophisticated in that they represent a specific numerical score, and the distance between points is assumed to be equal.
6. Ordinal data rank the elements in some logical order, but without knowing the rela- tive difference between ranks.
5. Continuous level data can be one of three types: ordinal, interval, or ratio.
4. For categorical data, each variable is com- prised of two or more classes or categories that should be mutually exclusive, exhaus- tive, and equivalent.
3. Discrete data are known as categorical or nominal data and describe the presence or absence of some characteristic or attribute.
2. Measurement allows researchers to make comparisons.
1. Research relies on measurement.
Oversimplifying negative or inconclusive results without looking for weakness in the research process (inappropriate theory or hy- potheses, inappropriate methodology, poor measurement, faulty analysis)
Not adequately explaining contradictory or unanticipated findings
Accepting data results as firm conclusions without examining alternative interpretations
Drawing sweeping conclusions from nonrep- resentative data
To whom do the conclusions apply?
Is there anything missing that might be important?
Do their conclusions fit with other known information about the issue or subject?
Do I agree with their conclusions?
How does their interpretation fit with the questions asked?
What meaning did the researchers infer from the results?
What did the researchers find?
How much confidence do I have in the data collection methods and statistical analyses?
What questions did the researchers ask?
Showing 1800 - 1900
of 2089
First
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Step by Step Answers
Get 50% OFF
Claim Now
