infer 0.4.0 2018-11-15

Breaking changes

  • Changed method of computing two-sided p-value to a more conventional one. It also makes get_pvalue() and visualize() more aligned (#205).

Deprecation changes

New functions


  • Account for NULL value in left hand side of formula in specify() (#156) and type in generate() (#157).
  • Update documentation code to follow tidyverse style guide (#159).
  • Remove help page for internal set_params() (#165).
  • Fully use {tibble} (#166).
  • Fix calculate() to not depend on order of p for type = "simulate" (#122).
  • Reduce code duplication (#173).
  • Make transparancy in visualize() to not depend on method and data volume.
  • Make visualize() work for “One sample t” theoretical type with method = "both".
  • Add stat = "sum" and stat = "count" options to calculate() (#50).

infer 0.3.1 2018-08-06

  • Stop using package {assertive} in favor of custom type checks (#149)
  • Fixed t_stat() to use ... so var.equal works
  • With the help of @echasnovski, fixed var.equal = TRUE for specify() %>% calculate(stat = "t")
  • Use custom functions for error, warning, message, and paste() handling (#155)

infer 0.3.0 2018-07-11

  • Added conf_int logical argument and conf_level argument to t_test()
  • Switched shade_color argument in visualize() to be pvalue_fill instead since fill color for confidence intervals is also added now
  • Shading for Confidence Intervals in visualize()
    • Green is default color for CI and red for p-values
    • direction = "between" to get the green shading
    • Currently working only for simulation-based methods
  • Implemented conf_int() function for computing confidence interval provided a simulation-based method with a stat variable
  • Implemented p_value() function for computing p-value provided a simulation-based method with a stat variable
  • Implemented Chi-square Goodness of Fit observed stat depending on params being set in hypothesize with specify() %>% calculate() shortcut
  • Removed “standardized” slope $t$ since its formula is different than “standardized” correlation and there is no way currently to give one over the other
  • Implemented correlation with bootstrap CI and permutation hypothesis test
  • Filled the type argument automatically in generate() based on specify() and hypothesize()
    • Added message if type is given differently than expected
  • Implemented specify() %>% calculate() for getting observed statistics.
    • visualize() works with either a 1x1 data frame or a vector for its obs_stat argument
    • Got stat = "t" working
  • Refactored calculate() into smaller functions to reduce complexity
  • Produced error if mu is given in hypothesize() but stat = "median" is provided in calculate() and other similar mis-specifications
  • Tweaked chisq_stat() and t_stat() to match with specify() %>% calculate() framework
    • Both work in the one sample and two sample cases by providing formula
    • Added order argument to t_stat()
  • Added implementation of one sample t_test() by passing in the mu argument to t.test from hypothesize()
  • Tweaked pkgdown page to include ToDo’s using {dplyr} example

infer 0.2.0 2018-05-15

  • Switched to !! instead of UQ() since UQ() is deprecated in {rlang} 0.2.0
  • Added many new files:,, and
  • Updated README file with more development information
  • Added wrapper functions t_test() and chisq_test() that use a formula interface and provide an intuitive wrapper to t.test() and chisq.test()
  • Created stat = "z" and stat = "t" options
  • Added many new arguments to visualize() to prescribe colors to shade and use for observed statistics and theoretical density curves
  • Added check so that a bar graph created with visualize() if number of unique values for generated statistics is small
  • Added shading for method = "theoretical"
  • Implemented shading for simulation methods w/o a traditional distribution
    • Use percentiles to determine two-tailed shading
  • Changed method = "randomization" to method = "simulation"
  • Added warning when theoretical distribution is used that assumptions should be checked
  • Added theoretical distributions to visualize() alone and as overlay with current implementations being
    • Two sample t
    • ANOVA F
    • One proportion z
    • Two proportion z
    • Chi-square test of independence
    • Chi-square Goodness of Fit test
    • Standardized slope (t)

infer 0.1.1 2018-01-22

  • Added additional tests
  • Added order argument in calculate()
  • Fixed bugs post-CRAN release
  • Automated travis build of pkgdown to gh-pages branch

infer 0.1.0 2018-01-08

  • Altered the way that successes are indicated in an infer pipeline. They now live in specify().
  • Updated documentation with examples
  • Created pkgdown site materials

infer 0.0.1 Unreleased

  • Implemented the “intro stats” examples for randomization methods