Description Usage Arguments Details Value Examples

This function displays d and non-central confidence interval for single t estimated from the t-statistic.

1 | ```
d.single.t.t(t, n, a = 0.05)
``` |

`t` |
t-test value |

`n` |
sample size |

`a` |
significance level |

To calculate d, the t-statistic is divided by the square root of the sample size.

d = t / 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 |

`n` |
sample size |

`df` |
degrees of freedom (sample size - 1) |

`t` |
sig stats |

`p` |
p-value |

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

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
#A school has a gifted/honors program that they claim is
#significantly better than others in the country. The gifted/honors
#students in this school scored an average of 1370 on the SAT,
#with a standard deviation of 112.7, while the national average
#for gifted programs is a SAT score of 1080.
gift = t.test(singt_data, mu = 1080, alternative = "two.sided")
#According to a single-sample t-test, the scores of the students
#from the program were significantly higher than the national
#average, t(14) = 9.97, p < .001.
#You can type in the numbers directly as shown below, or refer
#to your dataset within the function.
d.single.t.t(t = 9.968, n = 15, a = .05)
d.single.t.t(9.968, 15, .05)
d.single.t.t(gift$statistic, length(singt_data$SATscore), .05)
``` |

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