Question

Scales that use response categories ranging from 1 to 5 (with labels ranging from 1 for "completely agree" to 5 for "completely disagree") are called a. ratio scales. b. Likert scales. c. face valid. d. dichotomous.

Short answer

b. Likert scales.

Step-by-step solution

Understanding Scale Types

Start by understanding the different types of scales mentioned: - **Ratio scales** have a true zero point and the differences between measures are meaningful. It is usually used for measurements like weight or height. - **Dichotomous scales** have only two response options, like yes/no or true/false. - **Face validity** refers to how a test appears to measure what it's supposed to measure, not the scale itself. - **Likert scales** have multiple response options that capture the level of agreement or disagreement.

Review the Definitions

Review the definition of a Likert scale, which is used to measure attitudes or opinions with a range of responses labeled from strong agreement to strong disagreement. This matches the type described in the problem, with responses ranging from 1 (completely agree) to 5 (completely disagree).

Match the Problem Description

Compare the problem's scale description (1 for "completely agree" to 5 for "completely disagree") with the typical format for a Likert scale. This format shows incremental levels of agreement or disagreement, confirming it as a Likert scale.

Key concepts

Scale Types

When discussing measurement scales in surveys and research, it is essential to grasp the different types of scales available. Each type serves a unique purpose and is suitable for different data collection needs.
Understanding scale types helps researchers choose the right one for their study.

• Ratio Scales: These scales are quite informative as they have a true zero point. This means that things like weight, height, or income can be measured meaningfully. For instance, if one person weighs zero, it means they have no weight, which makes logical sense.
• Dichotomous Scales: These are the simplest kinds of scales, allowing only two response choices. Examples include yes/no or true/false questions. They are useful when only absolute decisions are needed.
• Likert Scales: These are highly popular in measuring attitudes and opinions because they provide multiple response options that show varying degrees of feeling. By having a range like 'completely agree' to 'completely disagree,' a Likert scale effectively nuances people's perceptions.
• Face Validity: Although not an actual scale type, it's an important concept referring to whether a test appears to measure what it claims to measure. It's more about initial perception than technical usability.

Response Categories

Response categories are crucial when designing surveys or questionnaires. They define the options available for participants to express their opinions or experiences. Well-constructed categories ensure data collected is both reliable and valid.
Response categories should be clear, exhaustive, and mutually exclusive.

• Clear Labels: Each response should be easily understood by respondents. For example, in a Likert scale, labels like 'completely agree' to 'completely disagree' are descriptive and straightforward.
• Exhaustive Options: All potential responses should be covered by the provided categories. This ensures participants can accurately express their thoughts.
• Mutually Exclusive: Respondents should be able to choose only one category that best represents their opinion or situation. Overlapping categories can lead to confusion and unreliable data.

Measurement Scales

Measurement scales are vital tools in data collection, allowing researchers to understand and quantify abstract concepts like opinions, attitudes, or behavioral intentions.
Choosing the right measurement scale depends on the research objective and the kind of data needed.

• Nominal Scales: Used for labeling variables without any quantitative value, such as gender or nationality. They categorize data without putting them in an order.
• Ordinal Scales: These assign a rank order to items. For example, first, second, and third place in a race indicate order, but not the gap between each position.
• Interval Scales: Allow for measurement of the distances between points, but lack a true zero point. An instance of this is temperature scales in Celsius or Fahrenheit.
• Ratio Scales: As mentioned earlier, these have all the features of interval scales, including a meaningful zero. It makes them excellent for precise measurements, such as weight or time.

Using the correct scale is essential for obtaining meaningful and useful research data.