Reduce amount of measurement error

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Questions

1. The term used to suggest that using several measurement alternatives (methods and measures) will reduce the amount of measurement error is:

Multiplication
Replication
Redundancy
Triangulation

2. Suppose we want to find out a person's knowledge of American history. We have the person multiple-choice test and then complete an essay exam that covers the same information. We expect that the scores will be similar. This form of measurement reliability is known as:

Test-retest
Parallel forms
Split halves
Inter-rater

3. The quality that encourages respondents to answer in a particular way to avoid or support a particular point of view is called:

Random error
Pretesting
Transparency
Bias

4. What is the main difference between closed-ended and open-ended questions?

5. When we believe that our instrument captures a concept consistently when measured against a known-standard, we are speaking of what type of validity?

Criterion-related validity
Content validity
Face validity
Construct validity

6. Suppose we have two people watch a videotaped interview. Each rates the interviewer's performance on an instrument. Each has been trained to evaluate such interviews. We are interested to see how well these two individuals compare in their scoring of the same videotape. What kind of reliability is this?

Construct validity
Inter-rater reliability
Split halves reliability
Test-retest reliability

7. When a question asks the respondent to what extent she or he agrees with a statement (typically indicated by "strongly agree," "agree," "neutral," "disagree," or "strongly disagree"), what kind of scaling format is being used?

Likert
Guttman
Pilot
Thurstone

8. There are both random and systematic forms of measurement error. According to your textbook, which type would be indicated by using a yardstick that is actually 36.75 inches long?

9. What is the level of measurement in which there is a meaningful zero point?

Interval
Nominal
Ordinal
Ratio

10. The level of measurement represented by variables that can be categorized but not ranked is:

Criterion-related validity
Content validity
Face validity
Construct validity

Reference no: EM133385365

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