## One Sample T-Test

The Student’s One-sample t-test is used to test the null hypothesis that the true mean is equal to a particular value (typically zero). A low p-value suggests that the null hypothesis is not true, and therefore the true mean must be different from the test value.

The Student’s One-sample t-test assumes that the data are from a normal
distribution – in the case that one is unwilling to assume this, the
non-parametric Wilcoxon signed-rank can be used in it’s place (However,
note that the Wilcoxon signed-rank has a slightly different null
hypothesis; that the *median* is equal to the test value).

### Example usage

### Arguments

data | the data as a data frame |

vars | a vector of strings naming the variables of interest in data |

students | TRUE (default) or FALSE, perform Student's t-tests |

bf | TRUE or FALSE (default), provide Bayes factors |

bfPrior | a number between 0.5 and 2.0 (default 0.707), the prior width to use in calculating Bayes factors |

wilcoxon | TRUE or FALSE (default), perform Wilcoxon signed rank tests |

testValue | a number specifying the value of the null hypothesis |

hypothesis | 'dt' (default), 'gt' or 'lt', the alternative hypothesis; different to testValue, greater than testValue, and less than testValue respectively |

norm | TRUE or FALSE (default), perform Shapiro-wilk tests of normality |

TRUE or FALSE (default), provide a Q-Q plot of residuals | |

meanDiff | TRUE or FALSE (default), provide means and standard deviations |

ci | TRUE or FALSE (default), provide confidence intervals for the mean difference |

ciWidth | a number between 50 and 99.9 (default: 95), the width of confidence intervals |

effectSize | TRUE or FALSE (default), provide Cohen's d effect sizes |

ciES | TRUE or FALSE (default), provide confidence intervals for the effect-sizes |

ciWidthES | a number between 50 and 99.9 (default: 95), the width of confidence intervals for the effect sizes |

desc | TRUE or FALSE (default), provide descriptive statistics |

plots | TRUE or FALSE (default), provide descriptive plots |

miss | 'perAnalysis' or 'listwise', how to handle missing values; 'perAnalysis' excludes missing values for individual dependent variables, 'listwise' excludes a row from all analyses if one of its entries is missing. |

mann |

### Returns

A results object containing:

results$ttest | a table |

results$normality | a table |

results$descriptives | a table |

results$plots | an image |

results$qq | an array of images |

Tables can be converted to data frames with asDF or as.data.frame(). For example:

results$ttest$asDF

as.data.frame(results$ttest)

Elements in arrays can be accessed with [[n]]. For example:

results$qq[[1]] # accesses the first element