qualitative variable

Examples of qualitative variable in the following topics:

• Qualitative Variable Models

  • Dummy, or qualitative variables, often act as independent variables in regression and affect the results of the dependent variables.
  • Dummy variables are "proxy" variables, or numeric stand-ins for qualitative facts in a regression model.
  • One type of ANOVA model, applicable when dealing with qualitative variables, is a regression model in which the dependent variable is quantitative in nature but all the explanatory variables are dummies (qualitative in nature).
  • This type of ANOVA modelcan have differing numbers of qualitative variables.
  • An example with two qualitative variables might be if hourly wages were explained in terms of the qualitative variables marital status (married / unmarried) and geographical region (North / non-North).

• Variables

  • An important distinction between variables is between qualitative variables and quantitative variables.
  • Qualitative variables are those that express a qualitative attribute such as hair color, eye color, religion, favorite movie, gender, and so on.
  • The values of a qualitative variable do not imply a numerical ordering.
  • Qualitative variables are sometimes referred to as categorical variables.
  • The variable "type of supplement" is a qualitative variable; there is nothing quantitative about it.

• Measures of Variability of Qualitative and Ranked Data

  • Variability for qualitative data is measured in terms of how often observations differ from one another.
  • The study of statistics generally places considerable focus upon the distribution and measure of variability of quantitative variables.
  • A discussion of the variability of qualitative--or categorical-- data can sometimes be absent.
  • In such a discussion, we would consider the variability of qualitative data in terms of unlikeability.
  • It is the simplest measure of qualitative variation.

• Quantitative or Qualitative Data?

  • Different statistical tests are used to test quantitative and qualitative data.
  • Qualitative (categorical) research, on the other hand, asks broad questions and collects word data from participants.
  • Examples of qualitative variables are male/female, nationality, color, et cetera.
  • One of the most common statistical tests for qualitative data is the chi-square test (both the goodness of fit test and test of independence).
  • A common case for this test is where the events each cover an outcome of a categorical variable.

• Types of Variables

  • A continuous variable is a numeric variable.
  • A discrete variable is a numeric variable.
  • Therefore, categorical variables are qualitative variables and tend to be represented by a non-numeric value.
  • An ordinal variable is a categorical variable.
  • A nominal variable is a categorical variable.

• Describing Qualitative Data

  • When the categories may be ordered, these are called ordinal variables.
  • Categorical variables that judge size (small, medium, large, etc.) are ordinal variables.
  • Deciding what is a variable, and how to code each subject on each variable, is more difficult in qualitative data analysis.
  • Concept formation is the creation of variables (usually called themes) out of raw qualitative data.
  • It is more sophisticated in qualitative data analysis.

• Quantitative and Qualitative

  • For instance, social class, following the quantitative approach, can be divided into different groups - upper-, middle-, and lower-class - and can be measured using any of a number of variables or a combination thereof: income, educational attainment, prestige, power, etc.
  • Qualitative methods of sociological research tend to approach social phenomena from the Verstehen perspective.
  • While qualitative methods may be used to propose or explore relationships between variables, these studies typically focus on explicating the realities people experience that lie at the heart or foundation of such relationships rather than focusing on the relationships themselves.
  • Further, qualitative sociologists typically reject measurement or quantities (essential to quantitative approaches) and the notion or belief in causality (e.g., qualitative sociologists generally argue that since there is no demonstrated possibility of ever exploring all potential variables or influences in one study, causality is always incomplete and beyond empirical means).
  • They view quantitative and qualitative approaches as complementary.

• Quantitative vs. Qualitative Research

  • Both quantitative and qualitative models seek to explain patterns in behavior, but the former is mathematical and the latter is more descriptive.
  • Qualitative methods produce information only on the particular cases studied, and any more general conclusions are only hypotheses.
  • Qualitative researchers aim to gather an in-depth understanding of human behavior and the reasons that govern it.
  • The qualitative method investigates the why and how of consumer behavior, not just what, where, when.
  • The Following Are Some Examples of Qualitative Approaches Used in Collecting Data:

• Correlation and Causation

  • While these terms are rarely used in qualitative science, they lie at the heart of quantitative methods, and thus constitute a cornerstone of scientific practice.
  • A positive correlation means that as one variable increases (e.g., ice cream consumption) the other variable also increases (e.g., crime).
  • Causation refers to a relationship between two (or more) variables where one variable causes the other.
  • change in the independent variable must precede change in the dependent variable in time
  • it must be shown that a different (third) variable is not causing the change in the two variables of interest (a.k.a., spurious correlation)

• Graphs of Qualitative Data

  • Recall the difference between quantitative and qualitative data.
  • Qualitative data are measures of types and may be represented as a name or symbol.
  • Variance and standard deviation require the mean to be calculated, which is not appropriate for categorical variables as they have no numerical value.
  • There are a number of ways in which qualitative data can be displayed.
  • The qualitative data results were displayed in a frequency table.