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Should you Normalise categorical data?
There is no need to normalize categorical variables. You are not very explicit about the type of analysis you are doing, but typically you are dealing with the categorical variables as dummy variables in the statistical analysis.
What does it mean if a variable is categorical or continuous?
Categorical variables contain a finite number of categories or distinct groups. Continuous variables are numeric variables that have an infinite number of values between any two values. A continuous variable can be numeric or date/time. For example, the length of a part or the date and time a payment is received.
What is the correlation between continuous and categorical variables?
Correlation between continuous and categorial variables •Point Biserial correlation – product-moment correlation in which one variable is continuous and the other variable is binary (dichotomous) – Categorical variable does not need to have ordering – Assumption: continuous data within each group created by the binary variable are normally
Can a continuous data type be converted to categorical?
Time is a special case, and continuous can always be converted into categorical (e.g., you might classify age into age groups or weight into low/medium/high, etc.). But the underlying data still has a type that is either quantitive or categorical.
Which is the simplest form of categorical variable?
The simplest form of categorical variable is an indicator variable that has only two values. The two values are typically 0 and 1, although other values are used at times. Other categorical variables take on multiple values. These values are often expressed using descriptive character strings.
Can you treat profit as a continuous variable?
This changes the type of chart we want to a line chart. Profit is now on the vertical axis, but it is still a continuous variable. We might treat time as categorical, which would give us another bar chart, perhaps with one bar per month (or whatever granularity we want). But I decided to treat time as continuous here, which results in a line chart.
https://www.youtube.com/watch?v=vrWYw8d2830