is age a quantitative or qualitative variable?
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In our medical example, age is an example of a quantitative variable because it can take on multiple numerical values. It also makes sense to think about it in numerical form; that is, a person can be 18 years old or 80 years old. Weight and height are also examples of quantitative variables.
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What's the difference between qualitative and quantitative research? ... Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.
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Examples of categorical variables are race, sex, age group, and educational level. While the latter two variables may also be considered in a numerical manner by using exact values for age and highest grade completed, it is often more informative to categorize such variables into a relatively small number of groups.
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Start with yourself as an example. To acquire qualitative data, consider identifiers like the color of your clothes, type of hair, and nose shape. For quantitative data, consider measurables like your height, weight, age, and shoe size.
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Qualitative variables take on values that are names or labels. The color of a ball (e.g., red, green, blue) or the breed of a dog (e.g., collie, shepherd, terrier) would be examples of qualitative or categorical variables. ... Quantitative variables are numeric. They represent a measurable quantity.
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Age is frequently collected as ratio data, but can also be collected as ordinal data. ... Variables that are naturally ordinal can't be captured as interval or ratio data, but can be captured as nominal.
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Quantitative Variables - Variables whose values result from counting or measuring something. Qualitative Variables - Variables that are not measurement variables. Their values do not result from measuring or counting. Designator - Values that are used to identify individuals in a table.
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Consider the variable age. Age is frequently collected as ratio data, but can also be collected as ordinal data. ... However, many variables that get captured as ordinal have a similar variable that can be captured as interval or ratio data, if you so choose.
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Psykolord1989 . Answer: Continuous if looking for exact age, discrete if going by number of years. If a data set is continuous, then the associated random variable could take on any value within the range.
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Consider the variable age. Age is frequently collected as ratio data, but can also be collected as ordinal data. ... Variables that are naturally ordinal can't be captured as interval or ratio data, but can be captured as nominal.
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Qualitative v. There are two general types of data. Quantitative data is information about quantities; that is, information that can be measured and written down with numbers. Some examples of quantitative data are your height, your shoe size, and the length of your fingernails.
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Participants were categorized by age into young adults (ages 18-35 years; n = 97), middle-aged adults (ages 36-55 years, n = 197), and older adults (aged older than 55 years, n = 49). Differences in demographics, gambling variables, and ASI composite scores were compared across the groups.
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Question: Determine Whether The Variable Is Qualitative Or Quantitative. Street Name Of Address Is The Variable Qualitative Or Quantitative? A. The Variable Is Quantitative Because It Is An Attribute Characteristic B.
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['Age is an issue of mind over matter. ... ', 'Age is just a number for me! ... ', "I don't look my age, I don't feel my age and I don't act my age. ... ", 'Age is just a number, maturity is a choice. ... ', 'Age is just a number, not a state of mind or a reason for any type of particular behaviour.']
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Qualitative vs. quantitative research. When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.
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Quantitative Data. Qualitative data is descriptive data like color, taste, texture, smell, etc. Quantitative data, on the other hand, is data that is measurable.
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It's meaningful to ask for height at (say) 2013.5, that would just be on June 30, 2018. So year is a discretized measure of a continuous interval variable, so quantitative. Year can also be an ordinal variable.