Is regression or ANOVA the right approach for determining RRP based on a set of RRPs associated with categorical variables Basically I have scraped some retail site data and I would like to know if this is a regression problem:
If I have data from the website about shoes like RRP, what brand they are, what colour they are and what size and I collate that data to build a model around such that I can give the model known variables about a new pair of shoes (brand, size colour) to determine it's likely RRP based on the set of shoes i already know all the variables and RRP for, should I use ANOVA or regression. My reasonings for regression is that it seems like a classic problem in that price is a continuous variable. But I'm unsure to go about this, a lot of the regression examples i see use contiuous variables for both the predictor and outcome variables maybe ANOVA is better?
ANOVA is a linear regression...a regression on categorical variables.
Regressions can have any mix of continuous and categorical variables. Some, like ANOVA and ANCOVA, have special names that you may want to use when you're communicating with people who have less training in statistics and don't know how to unify them with linear regression.