NATURE OF VARIABLES | Kinds of Variables and their Uses - Practical Research 2

Gine Castillo
28 Oct 202011:59

Summary

TLDRIn this video, Jane Castillo explains the concept of variables, defining them as elements that can take on multiple values, such as words or numbers. She categorizes variables into qualitative and quantitative types, further detailing subtypes like discrete, continuous, nominal, ordinal, and dichotomous variables. Castillo also explains independent, dependent, and extraneous variables, with examples illustrating their use in research. The video aims to help viewers understand these concepts in preparation for conducting their own research. Viewers are encouraged to subscribe for more educational content.

Takeaways

  • πŸ˜€ Variables are entities that can take more than one value, represented by words or numbers.
  • πŸ“Š Variables can be categorized into quantitative (numerical) and qualitative (categorical).
  • πŸ”’ Quantitative variables include discrete (whole numbers) and continuous (fractions or ranges).
  • πŸ“ˆ Continuous variables like height and weight can be measured in fractions and have both positive and negative values.
  • πŸ“š Qualitative variables are not expressed in numbers but in categories or descriptions.
  • πŸ‘« Dichotomous variables have only two attributes, such as 'yes/no' or 'male/female'.
  • πŸ“‹ Ordinal variables are ranked in an order, such as educational attainment or income levels.
  • πŸ§ͺ Independent variables influence outcomes, while dependent variables rely on independent variables for their results.
  • πŸ” Extraneous variables are factors that could influence the outcome but are not manipulated by the researcher.
  • ❗ Confounding variables are specific types of extraneous variables that cannot be controlled and may affect the research validity.

Q & A

  • Who is the speaker in the video, and what topics does she cover on her channel?

    -The speaker is Jane Castillo, and she covers topics related to English and research on her channel.

  • How does Bernard (1994) define a variable?

    -Bernard (1994) defines a variable as something that can take more than one value, which can be represented by words or numbers.

  • What are some examples of variables expressed in words?

    -Examples of variables expressed in words include sex (male or female), occupation, mode of transportation, school, and educational attainment.

  • What are attributes, and how are they related to variables?

    -Attributes are specific values associated with a variable. For example, the variable 'sex' can have two attributes: male and female.

  • What are the two main types of variables according to their nature?

    -The two main types of variables according to their nature are quantitative (numerical) and qualitative (categorical).

  • What is the difference between discrete and continuous variables?

    -Discrete variables are countable and have whole numbers, while continuous variables can take on fractions and are measured in ranges, often representing measurements like height, weight, or temperature.

  • What are dichotomous variables?

    -Dichotomous variables consist of two categories, such as yes/no questions, sex (male or female), or type of school (private or public).

  • What is the difference between nominal and ordinal variables?

    -Nominal variables represent categories that cannot be ordered, like sex (male or female), while ordinal variables can be ranked or ordered, such as educational attainment or family income levels.

  • What are independent and dependent variables in a study?

    -Independent variables are those that cause or influence outcomes, while dependent variables are the results or outcomes that depend on the independent variables.

  • What are extraneous and confounding variables, and how do they affect research?

    -Extraneous variables are factors that may influence the outcome of a study but are not part of the main variables being studied. Confounding variables are a special type of extraneous variable that researchers cannot control, and they may threaten the validity of experimental research.

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Related Tags
Research VariablesQuantitative StudyQualitative VariablesEducational ResearchIndependent VariablesDependent VariablesDiscrete DataContinuous DataConfounding FactorsPractical Research