# d.single.t: d for Single t from Means In MOTE: Effect Size and Confidence Interval Calculator

## Description

This function displays d and non-central confidence interval for single t from means.

## Usage

 1 d.single.t(m, u, sd, n, a = 0.05)

## Arguments

 m sample mean u population mean sd sample standard deviation n sample size a significance level

## Details

To calculate d, the population is subtracted from the sample mean, which is then divided by the standard deviation.

d = (m - u) / sd

## Value

 d effect size dlow lower level confidence interval d value dhigh upper level confidence interval d value m sample mean sd standard deviation of the sample se standard error of the sample Mlow lower level confidence interval of the sample mean Mhigh upper level confidence interval of the sample mean u population mean n sample size df degrees of freedom (n - 1) t t-statistic 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

## Examples

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #The following example is derived from the "singt_data" dataset included #in the MOTE library. #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") #You can type in the numbers directly as shown below, #or refer to your dataset within the function. d.single.t(m = 1370, u = 1080, sd = 112.7, n = 14, a = .05) d.single.t(1370, 1080, 112.7, 100, .05) d.single.t(gift\$estimate, gift\$null.value, sd(singt_data\$SATscore), length(singt_data\$SATscore), .05)

MOTE documentation built on May 2, 2019, 5:51 a.m.