Determine appropriate measurement scales for a given research design.
Mapping rules (four assumptions)
Numbers are used to classify, group, or sort responses. No order exists. Numbers are ordered. One number is greater than, less than, or equal to another number. Differences between numbers are ordered. The difference between any pair of numbers is greater than, less than, or equal to the difference between any other pair of numbers. The number series has a unique origin indicates by the number zero. This is an absolute and meaningful zero point.
Types of measurement scales
Nominal scales
Ordinal scales
Interval scales
Ratio scales
Sources of measurement differences
Error sources
The respondent
Situational factors
The measurer
The instrument
The characteristics of good measurement
Validity is the extent to which a test measures what we actually wish to measure.
Content validity
Criterion-related validity
Construct validity
Reliability has to do with the accuracy and precision of a measurement procedure.
Stability
Equivalence
Internal consistency
Practicality is concerned with a wide range of factors of economy, convenience, and interpretability.
Economy
Convenience
Interpretability
Selecting a measurement scale
Research objectives
Response types
Data properties
The Research paper on Construct validity
Most, but not all, tests are designed to measure skills, abilities, or traits that are and are not directly observable. The process of using a test score as a sample of behavior in order to draw conclusions about a larger domain of behaviors is characteristic of most educational and psychological tests (Miller, et. al., 2013). Responsible test developers and publishers must be able to demonstrate ...
Number of dimensions
Balanced or unbalanced
Forced or unforced choices
Number of scale points
Rater errors
Rating scales
Simple attitude scales (simple category scale/dichotomous)
Multiple-choice, single-response scale
Multiple-choice, multiple-response scale
Likert scale summated rating
Semantic differential scale
Numerical scale
Multiple rating list scale
Staple scale
Constant-sum scale
Graphic rating scale
Construct effective questionnaires and surveys
Error in communication research: error sources
Interview error
Failure to secure full participant cooperation (sampling error) Failure to record answers accurately and completely (data entry error) Failure to consistently execute interview procedures
Failure to establish appropriate interview environment
Falsification of individual answers or whole interviews
Inappropriate influencing behavior
Physical presence bias
Participant error (broad conditions)
The participant must possess the information being targeted by the investigative questions. The participant must understand his or her role in the interview as the provider of accurate information. The participant must have adequate motivation to cooperate.
Participation-based errors (three influencing factors)
The participant must believe that the experience will be pleasant and satisfying. The participant must believe that answering the survey is an important and worthwhile use of his or her time. The participant must dismiss any mental reservations that he or she might have about participation.
Response-based errors
Response strategy
Free-response question
Dichotomous question
Multiple-choice question (single response)
Checklist
Rating question (rating grid)
Ranking question
Conduct hypothesis testing using one- and two sample t-tests.
Performance of hypothesis testing regarding one-sample mean
One-sample mean hypothesis testing
Significance levels
p-value
t-statistic
z-statistic
Performance of hypothesis testing regarding one-sample proportion
The Term Paper on Testing hypothesis
Introduction to Hypothesis Testing 8.1 Inferential Statistics and Hypothesis Testing LEARNING OBJECTIVES 8.2 Four Steps to Hypothesis Testing After reading this chapter, you should be able to: 8.3 Hypothesis Testing and Sampling Distributions 8.4 Making a Decision: Types of Error 8.5 Testing a Research Hypothesis: Examples Using the z Test 8.6 Research in Focus: Directional Versus Nondirectional ...
One-sample proportion hypothesis testing
Significance levels
p-value
Performance of hypothesis testing regarding two-sample means
Two-sample means hypothesis testing
Significance levels
p-value
t-statistic
z-statistic
