Q: Data at the ordinal level are quantitative only?

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Gender is nominal. Nominal is categorical only; no ordering scheme. Ordinal level of measurement places some order on the data, but the differences between the data can't be determined or are meaningless.

Mode is the only measure of central tendency to measure quantitative dataor qualitative data.

Quantitative means measurable and/or a reference to a specific amount.Examples of quantitative data:3kg1l9lbsQualitative means data that are more easily (or only) expressed by description and not measurementsExamples of qualitative:"My ball is red.""That sword is sharp."

Quantitative data is data that is relating to, measuring, or measured by the quantity of something, rather than its quality. ex: the number of people in a townQualitative data is data that can be captured that is not numerical in nature ex: the color of people's skin.Thus, essentially the distinction is that quantitative data deals with numbers and numerical values of what is being tested, where as qualitative data deals with the quality of what is being tested.Qualitative data's description cannot be describe in numbers. Quantitative data's description ca only be described in numbers.

If the data are quantitative they must have a median. If there is no median it is only because the data are qualitative and, in that case, a box and whiskers plot is meaningless.

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False. Data at the ordinal level can be either quantitative or qualitative. In ordinal data, the categories have a meaningful order or rank, but the difference between the categories is not necessarily equal.

Gender is nominal. Nominal is categorical only; no ordering scheme. Ordinal level of measurement places some order on the data, but the differences between the data can't be determined or are meaningless.

Quantitative data

The main difference between qualititative and quantitative data is the numeric information. In quliatative data we only rely on information from the field which is not numeric and the quantitative data contains numerica data. That's why quantitative data is also know as mathematic dats.

Ordinal data has an inherent order, i.e. ranking, in its possible values. For example 'poor, fair, good, excellent' is ordinal becaused there is an assumption that the four possible values are higher from one to the next. It can be coded as 1,2,3,4 but there is no assumption of equal spacing. Nominal data has no inherent ranking, only labeling-e.g. 'apple, strawberry, orange'. The choices are three levels with no assumed value. Any numerical coding does not reflect any quantitative meaning. Georgette Asherman, Direct Effects, LLC

Mode is the only measure of central tendency to measure quantitative dataor qualitative data.

Quantitative data is measurable and numerical in nature. In contrast, qualitative data is any data that is not numerical and cannot be measured, only observed. Examples of quantitative data include age, height, year, and population. Examples of qualitative data include color, gender, country, and city.

Quantitative means measurable and/or a reference to a specific amount.Examples of quantitative data:3kg1l9lbsQualitative means data that are more easily (or only) expressed by description and not measurementsExamples of qualitative:"My ball is red.""That sword is sharp."

Quantitative data is data that is relating to, measuring, or measured by the quantity of something, rather than its quality. ex: the number of people in a townQualitative data is data that can be captured that is not numerical in nature ex: the color of people's skin.Thus, essentially the distinction is that quantitative data deals with numbers and numerical values of what is being tested, where as qualitative data deals with the quality of what is being tested.Qualitative data's description cannot be describe in numbers. Quantitative data's description ca only be described in numbers.

First let's look at what quantitative data is.Quantitative data are numeric.Discrete data are numeric data that have a finite number of possible values.So it is numerical data that can only have a finite number of possible values.One often used example of discrete quantitative data is the number 1,2 3, and 4 corresponding to strongly agree, agree, neutral, and don't agree,

In qualitative variables, nominal data involves categories with no inherent order, such as colors or types of fruit. Ordinal data, on the other hand, includes categories that have a meaningful order or ranking, such as education levels or customer satisfaction ratings.

If the data are quantitative they must have a median. If there is no median it is only because the data are qualitative and, in that case, a box and whiskers plot is meaningless.