My rule: Keep records and tax returns for years that include atypical transactions (sales or donations of property) and irregular income (stock option exercises, trust income, etc.) for six years after the filing date of the return. Keep a 2005 tax return that includes reporting of irregular items until April 2012.
Logistic regression was developed by statistician David Cox in 1958 (although much work was done in the single independent variable case almost two decades earlier). The binary logistic model is used to estimate the probability of a binary response based on one or more predictor (or independent) variables (features).
For nominal data, if the response is a binary variable (that is only two possible values such as graduate in four years or not), then, use Logistic regression model. If the response has more than two categories, use multinomial logistic regression. For ordinal data, if the response follows Poisson distribution, use Poisson regression model. In general, one can use log-linear models for ordinal data. In many applications, the relationship between response variable and predictors are not linear, but may be linearized. Generalized linear modeling techniques are useful.