## 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).

### 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 qq 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[] # accesses the first element