Chapter 6 - Measurement. After reading this chapter, you should be able to: Understand that measurement is a process; understand the principle that numbers have no inherent meaning until the researcher assigns or imposes meaning; develop categories for nominal data that are mutually exclusive, exhaustive, and equivalent; | Chapter 6 Measurement Associated with quantitative studies Numbers used as a tool for identifying and presenting information Links the conceptual to the empirical Necessary to conduct quantitative research Measurement Principles Numbers measure value, intensity, degree, depth, length, width, distance Descriptive and evaluative device Numbers have no value until we provide meaning Includes everything the researcher does to arrive at a number Details the operationalization of the variable Levels of Measurement Discrete or continuous Both representative of communication phenomena Each produces different kind of data How data are collected determines how they can be used in statistical analyses Discrete Data The presence or absence of some characteristic Also known as nominal or categorical data Categories Reflect different types not differing amounts Have no inherent value Must be mutually exclusive, exhaustive, and equivalent Continuous Level Data Reveals quantity, . | Chapter 6 Measurement Associated with quantitative studies Numbers used as a tool for identifying and presenting information Links the conceptual to the empirical Necessary to conduct quantitative research Measurement Principles Numbers measure value, intensity, degree, depth, length, width, distance Descriptive and evaluative device Numbers have no value until we provide meaning Includes everything the researcher does to arrive at a number Details the operationalization of the variable Levels of Measurement Discrete or continuous Both representative of communication phenomena Each produces different kind of data How data are collected determines how they can be used in statistical analyses Discrete Data The presence or absence of some characteristic Also known as nominal or categorical data Categories Reflect different types not differing amounts Have no inherent value Must be mutually exclusive, exhaustive, and equivalent Continuous Level Data Reveals quantity, intensity, or magnitude Values that differ in degree, amount, or frequency can be ordered on a continuum Three types Ordinal data Interval data Ratio data Ordinal Data Ranks elements in logical numerical order Sequence suggests value of data Ranking positions are relative Distance between ranks is unknown Zero does not exist Interval Data Identifies highest, next highest, and so on Identifies exact difference between and among scores Acknowledges zero Allows meaningful comparisons Likert-type scales Semantic differential scales Ratio Data All of the characteristics of interval data Zero is absolute Indicates complete lack of the variable measured Provides measure of degree to which something actually exists Validity Extent to which it measures what you want it to measure and not something else Validity is a matter of degree Internal validity Face validity Content validity Criterion-related validity: concurrent or predictive Construct validity Reliability Degree of .
