Adjusted R-square
Analysing qualitative data.
Analysing quantitative data
ANCOVA (Analyses of covariance)
ANOVA (Analyses of variance)
Applied research
Average
Bias
[...]
Quantitative value
A number is a quantitative datum. A qualitative datum is any other type of data or a number. A number is therefore also a qualitative datum.
The result of a measurement of a characteristic is a datum. Data can be qualitative or quantitative in nature. A qualitative datum is a word, a sentence or a piece of spoken or written text. A quantitative datum is a number.
A number can refer to an answer mentioned by the respondent from a (limited) list of possibilities (for example: 1 = very good, 2 = good, 3 = normal, 4 = bad, 5 = very bad) and that answer is stored in a data file. The researcher can therefore record a respondent's answer as a number or as a word. This is material for a confusion of speech: is it now a quantitative or a qualitative datum? If the answer is stored as a number then it is actually a quantitative datum, if it is stored in letters it is actually a qualitative datum.
But now the following: if one asks about the age of the respondent, then that yields a number. This answer can be written down in letters (for example, 10 as ten and 89 as eighty-nine), which makes it a qualitative datum. This example makes something clear: every quantitative datum can also be written as a qualitative datum, but every qualitative datum cannot be written as a quantitative datum. If one codes qualitative data as a quantitative data, this is usually accompanied by information loss (reduction) and one needs a codebook to know what those numbers stand for.
Statistical methods are used to analyze quantitative data. Which analyzes are allowed to be applied depends on the scale at which the variable has been measured. The researcher must be careful with arithmetic operations. Two children from the first marriage and one child from the second is three children in total (2 + 1 = 3). But, bad and very bad is not neutral (1 + 2 3). And the mean of very poor and very good ((1 + 5) / 2 = 3) is not the same as no opinion.
The fact that you have a quantitative data does not automatically mean that you are conducting a quantitative research. For the distinction between qualitative and quantitative research, very different characteristics are taken into account.
