Quantitative/Qualitative Research Password Version

The correct answer is "Numbers" because quantitative data is characterized by numerical values or measurements. This type of data can be expressed in terms of quantities or amounts, and can be manipulated mathematically or statistically. It is different from qualitative data, which is descriptive in nature and does not involve numerical values.

Qualitative data refers to non-numerical data that is collected through observations, interviews, or open-ended questions. It focuses on capturing the richness and depth of experiences, opinions, and behaviors. Text, pictures, videos, and sound recordings are examples of qualitative data as they provide detailed descriptions, visual representations, and audio recordings that can convey the nuances and context of the subject being studied. Equations, on the other hand, are typically used to represent quantitative data and are not considered qualitative data.

The correct answer is that the most fundamental difference between qualitative data and quantitative data is the type of judgment used to make meaning of the data and how the data are manipulated. Qualitative data is typically subjective and relies on interpretations and judgments made by researchers, while quantitative data is objective and relies on numerical measurements and statistical analysis. Additionally, qualitative data is often analyzed through coding and thematic analysis, while quantitative data is analyzed through statistical methods such as hypothesis testing and regression analysis.

The correct answer is (lowest) nominal-->ordinal-->interval-->ratio (highest). This sequence follows the logical progression of levels of measurement. Nominal level of measurement is the lowest, where variables are categorized into distinct groups with no quantitative value. Ordinal level adds the attribute of order or ranking to the categories. Interval level introduces equal intervals between the values, allowing for meaningful differences and addition/subtraction operations. Ratio level includes all the attributes of the previous levels and also has a true zero point, enabling multiplication/division operations and the use of inferential statistics.

Ratio data refers to data that has a true "0" point and can be manipulated mathematically. In this level of measurement, the numerical values have a meaningful ratio, allowing for comparisons and calculations such as addition, subtraction, multiplication, and division. Examples of ratio data include age, height, weight, and income.

In this question, the correct answer is "nominal". Nominal data refers to a level of measurement where numbers are used as labels or categories, rather than representing quantities or values. In a study, when numbers are used as labels instead of names, it indicates that the data is at a nominal level of measurement. This means that the numbers do not have any inherent order or magnitude and are simply used to categorize or identify different groups or variables.

A construct refers to the theoretical idea or concept that is being described or analyzed in the process of research. It represents an abstract concept that researchers aim to measure or characterize through data collection. Constructs are often used to represent complex phenomena that cannot be directly observed, such as intelligence or personality traits. By understanding and defining constructs, researchers can design appropriate methods and collect relevant data to answer their research questions.

Validity refers to the extent to which a research study measures what it intends to measure and accurately represents the true state of affairs. It is about the accuracy and soundness of the research findings, inferences, or conclusions. In other words, validity determines whether the results obtained from a study are reliable and can be generalized to the population or phenomenon being studied. It is an important aspect of research as it ensures that the study is meaningful, credible, and trustworthy.

The given answer correctly states that although some data are collected quantitatively, there are many qualitative judgments involved in how those responses are collected. This means that even when collecting quantitative data, researchers still need to make subjective judgments about the design, methodology, and interpretation of the data. Therefore, it is important to remember that qualitative judgments play a role in handling both qualitative and quantitative data.

Validity in research refers to the extent to which the findings and conclusions of a study are accurate, meaningful, and applicable to a larger population or context. It assesses whether the research methods and measures used are appropriate and reliable in capturing the phenomenon being studied. Validity determines the generalizability of the research, indicating how well the findings can be applied to other settings or populations. It is distinct from reliability, which focuses on the consistency and stability of the research measures. Therefore, the given answer accurately describes validity as the term refers to the meaningfulness of generalizing based on the research.