Description Usage Arguments Details Value Examples

This function displays d for Z-tests when all you have is the z-statistic. The normal confidence interval is also provided if you have sigma. If sigma is left blank, then you will not see a confidence interval.

1 |

`z` |
z statistic |

`sig` |
population standard deviation |

`n` |
sample size |

`a` |
significance level |

To calculate d, z is divided by the square root of N.

d = z / sqrt(N)

Learn more on our example page.

The effect size (Cohen's d) with associated confidence intervals and relevant statistics.

`d` |
effect size |

`dlow` |
lower level confidence interval d value |

`dhigh` |
upper level confidence interval d value |

`sigma` |
sample size |

`z` |
sig stats |

`p` |
p-value |

`n` |
sample size |

`estimate` |
the d statistic and confidence interval in APA style for markdown printing |

`statistic` |
the Z-statistic in APA style for markdown printing |

1 2 3 4 5 6 7 8 9 10 11 12 | ```
#A recent study suggested that students (N = 100) learning
#statistics improved their test scores with the use of
#visual aids (Z = 2.5). The population standard deviation is 4.
#You can type in the numbers directly as shown below,
#or refer to your dataset within the function.
d.z.z(z = 2.5, sig = 4, n = 100, a = .05)
d.z.z(z = 2.5, n = 100, a = .05)
d.z.z(2.5, 4, 100, .05)
``` |

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