Rename variables

src/stats/critical_values/chi_squared.js

@@ -2,25 +2,25 @@ import { getCriticalValue, getCriticalValuesMap } from './map.js'
 
 /* eslint-disable max-lines */
 // Return number to multiply variance with in order to get its confidence
-// interval for a given significance rate and size.
+// interval for a given significance level and size.
 // Uses the chi-squared distribution's critical value.
-export const getChiSquaredValue = function (size, significanceRate) {
+export const getChiSquaredValue = function (size, significanceLevel) {
   const degreesOfFreedom = size - 1
   const criticalValue = getCriticalValue(
     CHI_SQUARED_MAP,
     degreesOfFreedom,
-    significanceRate,
+    significanceLevel,
   )
   return degreesOfFreedom / criticalValue
 }
 
-// Chi-squared critical values, with specific significance rate, single-sided
+// Chi-squared critical values, with specific significance level, single-sided
 // TODO: more digits of precision
 // TODO: more values
 /* eslint-disable unicorn/numeric-separators-style */
 const CHI_SQUARED_RAW = [
   {
-    significanceRate: 0.025,
+    significanceLevel: 0.025,
     getMaxValue(degreesOfFreedom) {
       return degreesOfFreedom + 1
     },
@@ -296,7 +296,7 @@ const CHI_SQUARED_RAW = [
     },
   },
   {
-    significanceRate: 0.975,
+    significanceLevel: 0.975,
     getMaxValue(degreesOfFreedom) {
       return degreesOfFreedom - 1
     },

src/stats/critical_values/map.js

@@ -4,7 +4,7 @@
 // computing the real value with their underlying function. This is much faster
 // but less precise.
 // The pre-computed table is an array of objects with properties:
-//  - `significanceRate` {float}: from 0 to 1
+//  - `significanceLevel` {float}: from 0 to 1
 //  - `values` {object}:
 //     - keys are the degrees of freedom
 //     - values are the critical values
@@ -17,7 +17,7 @@ export const getCriticalValuesMap = function (criticalValuesRaw) {
 }
 
 const getCriticalValueEntry = function ({
-  significanceRate,
+  significanceLevel,
   getMaxValue,
   criticalValues,
 }) {
@@ -29,7 +29,7 @@ const getCriticalValueEntry = function ({
   const [impreciseEntriesMaxIndex] =
     impreciseEntries[impreciseEntries.length - 1]
   return [
-    roundDecimals(significanceRate),
+    roundDecimals(significanceLevel),
     { preciseMap, impreciseEntries, impreciseEntriesMaxIndex, getMaxValue },
   ]
 }
@@ -45,7 +45,7 @@ const isLastPreciseKey = function ([key], index, entries) {
 }
 
 // Retrieve a critical value given a specific degrees of freedom and
-// significance rate.
+// significance level.
 // There are three levels of precision depending on how high the numbers of
 // degrees of freedom are, since the pre-computed table cannot hard code all
 // possible values:
@@ -55,14 +55,14 @@ const isLastPreciseKey = function ([key], index, entries) {
 export const getCriticalValue = function (
   criticalValuesMap,
   degreesOfFreedom,
-  significanceRate,
+  significanceLevel,
 ) {
   const {
     preciseMap,
     impreciseEntries,
     impreciseEntriesMaxIndex,
     getMaxValue,
-  } = criticalValuesMap.get(roundDecimals(significanceRate))
+  } = criticalValuesMap.get(roundDecimals(significanceLevel))
 
   if (degreesOfFreedom > impreciseEntriesMaxIndex) {
     return getMaxValue(degreesOfFreedom)

src/stats/critical_values/student_t.js

@@ -4,19 +4,19 @@ import { getCriticalValue, getCriticalValuesMap } from './map.js'
 // Retrieve critical value of the Student's t distribution, two-tailed, for a
 // given degrees of freedom
 export const getStudentTValue = function (degreesOfFreedom) {
-  const singleSignificanteRate = (1 - SIGNIFICANCE_RATE) / 2
+  const singleSignificanteLevel = (1 - SIGNIFICANCE_LEVEL) / 2
   return getCriticalValue(
     STUDENT_T_MAP,
     degreesOfFreedom,
-    singleSignificanteRate,
+    singleSignificanteLevel,
   )
 }
 
-const SIGNIFICANCE_RATE = 0.95
+const SIGNIFICANCE_LEVEL = 0.95
 
 const STUDENT_T_RAW = [
   {
-    significanceRate: 0.025,
+    significanceLevel: 0.025,
     getMaxValue() {
       return MAX_T_VALUE
     },