T-Test with Plain-English Interpretation

Usage

ttest_interpret(
  x,
  y = NULL,
  mu = 0,
  paired = FALSE,
  conf.level = 0.95,
  var_name = "Variable"
)

Arguments

x: A numeric vector (group 1, or the only group for one-sample)
y: A numeric vector (group 2, for independent samples). Default NULL.
mu: Hypothesised mean for one-sample t-test. Default 0.
paired: Logical. TRUE for paired t-test. Default FALSE.
conf.level: Confidence level. Default 0.95.
var_name: Optional label for the report. Default "Variable"

Value

An object of class statease_ttest containing test results and interpretation. Use print() to display the formatted report.

Examples

result <- ttest_interpret(c(23,45,12,67,34), c(19,38,22,51,29))
#> Warning: Sample size in x is small (n < 10). Interpret results with caution.
#> Warning: Sample size in y is small (n < 10). Interpret results with caution.
print(result)
#> 
#> -- statease T-Test Report ----------------------------------------
#>   Test         : Independent Samples T-Test
#>   Variable     : Variable
#>   Groups       : Group 1: n = 5  |  Group 2: n = 5
#> -----------------------------------------------------------------
#>   t-statistic  : 0.396
#>   df           : 6.6
#>   p-value      : 0.7043
#>   95% CI      : [-22.146, 30.946]
#>   Cohen's d    : 0.251 (small effect)
#> -----------------------------------------------------------------
#>   Interpretation:
#>   The result is not statistically significant (p = 0.704 > alpha 0.05).
#>   Group 1 had a higher mean (36.20 vs 31.80).
#>   Effect size is small (d = 0.251).
#>   95% CI: true difference lies between -22.146 and 30.946.
#> -----------------------------------------------------------------
#>