# Two z-Approximation Tests

### Description

Calculates the Chi-square approximation to the z-test and the binomial approximation to the z-test.

### Usage

1 | ```
z_tests_cfa(observed, expected, ccor = FALSE, ntotal = sum(observed))
``` |

### Arguments

`observed` |
a vector giving the observed frequencies. |

`expected` |
a vector giving the expected frequencies. |

`ccor` |
either a logical (TRUE / FALSE) determining wether to apply a continuity correction or not. When set to |

`ntotal` |
optional a numeric giving the total number of observations. By default ntotal is calculated as |

### Details

An continuity correction can be applied to the binomial approximation – see argument `ccor`

.

### Value

a list with z an p-values.

### References

No references in the moment

### Examples

1 2 3 4 5 6 7 8 | ```
#######################################
# expected counts for LienertLSD data example.
designmatrix<-design_cfg_cfa(kat=c(2,2,2)) # generate an designmatrix (only main effects)
data(LienertLSD) # load example data
observed<-LienertLSD[,4] # extract observed counts
expected<-expected_cfa(des=designmatrix, observed=observed) # calculation of expected counts
z_tests_cfa(observed,expected)
#######################################
``` |