# dec_cor: Number of individuals for which the decision is correct. In riskyr: Rendering Risk Literacy more Transparent

## Description

`dec_cor` is a frequency that describes the number of individuals in the current population `N` for which the decision is correct/accurate (i.e., cases in which the decision corresponds to the condition).

## Usage

 `1` ```dec_cor ```

## Format

An object of class `numeric` of length 1.

## Details

Key relationships:

1. to probabilities: The frequency of `dec_cor` individuals depends on the population size `N` and the accuracy `acc`.

2. to other frequencies: In a population of size `N` the following relationships hold:

• `N = cond_true + cond_false` (by condition)

• `N = dec_pos + dec_neg` (by decision)

• `N = dec_cor + dec_err` (by correspondence of decision to condition)

• `dec_cor = hi + cr`

• `dec_err = mi + fa`

• `N = hi + mi + fa + cr` (by condition x decision)

3. correspondence: When not rounding the frequencies of `freq` then

`dec_cor = N x acc = hi + cr`

(i.e., `dec_cor` corresponds to the sum of true positives `hi` and true negatives `cr`.

Current frequency information is computed by `comp_freq` and contained in a list `freq`.

## References

Consult Wikipedia: Confusion matrix for additional information.

`is_freq` verifies frequencies; `num` contains basic numeric parameters; `init_num` initializes basic numeric parameters; `freq` contains current frequency information; `comp_freq` computes current frequency information; `prob` contains current probability information; `comp_prob` computes current probability information.
Other frequencies: `N`, `cond_false`, `cond_true`, `cr`, `dec_err`, `dec_neg`, `dec_pos`, `fa`, `hi`, `mi`
 ```1 2 3``` ```dec_cor <- 1000 * .50 # => sets dec_cor to 50% of 1000 = 500 cases. is_freq(dec_cor) # => TRUE is_prob(dec_cor) # => FALSE, as dec_cor is no probability (but acc, bacc/wacc ARE) ```