Pen Settings



CSS Base

Vendor Prefixing

Add External Stylesheets/Pens

Any URLs added here will be added as <link>s in order, and before the CSS in the editor. You can use the CSS from another Pen by using its URL and the proper URL extension.

+ add another resource


Babel includes JSX processing.

Add External Scripts/Pens

Any URL's added here will be added as <script>s in order, and run before the JavaScript in the editor. You can use the URL of any other Pen and it will include the JavaScript from that Pen.

+ add another resource


Add Packages

Search for and use JavaScript packages from npm here. By selecting a package, an import statement will be added to the top of the JavaScript editor for this package.


Auto Save

If active, Pens will autosave every 30 seconds after being saved once.

Auto-Updating Preview

If enabled, the preview panel updates automatically as you code. If disabled, use the "Run" button to update.

Format on Save

If enabled, your code will be formatted when you actively save your Pen. Note: your code becomes un-folded during formatting.

Editor Settings

Code Indentation

Want to change your Syntax Highlighting theme, Fonts and more?

Visit your global Editor Settings.


                  <script src=''></script>
  <script src=''></script>

  <div id='a_b_test_calculator' style="background-color: #eee;">
    <div id='myDiv'><!-- Plotly chart will be drawn inside this DIV --></div>

    <form name="calculateSignificanceLevelForm" onsubmit="return printFormInputs()">
      Sample Size A: <input type="number" name="n_a" value="500" max="99999">
      Success Rate A (%): <input type="number" min="0" max="1" step="0.00001" name="p_a" value="0.05">
      Sample Size B: <input type="number" name="n_b" value="100" max="99999">
      Success Rate B (%): <input type="number" min="0" max="1" step="0.00001" name="p_b" value="0.1">
      <input type="submit" value="Calculate the p-value" style="background-color: #4CAF50; color: #ffffff; border-color: #4CAF50;">


    <h3 id ="interpreting_the_results">Interpreting The Results</h3>
    <span id = "interpret_results">This section will populate after you complete the form above.</span>



<h3 id ="hypothesis_specification">Hypothesis Specification</h3>

<p><span style="text-decoration: underline;">Null Hypothesis</span>: Success Rate A ≥ Success Rate B<br><span style="text-decoration: underline;">Alternative Hypothesis</span>: Success Rate A &lt; Success Rate B<br><span style="text-decoration: underline;">Significance Level, ⍺</span>: 5%</p>


  <h3>Reference Inputs and Computed Statistics</h3>
  <p><span id = "inputs_and_statistics">This section will populate after you complete the form above.</span></p>


  function printFormInputs() {
    var significanceLevel = 0.05;
    var n_a = document.forms["calculateSignificanceLevelForm"]["n_a"].value;
    var p_a = document.forms["calculateSignificanceLevelForm"]["p_a"].value;
    var n_b = document.forms["calculateSignificanceLevelForm"]["n_b"].value;
    var p_b = document.forms["calculateSignificanceLevelForm"]["p_b"].value;

    // source:

    // Standard error of the difference between two sample proportions
    var pooledStandardError = Math.sqrt( ((p_a*(1-p_a))/n_a) + ((p_b*(1-p_b))/n_b) );
    var zStatistic = (p_a - p_b) / pooledStandardError;
    var pValue = ss.cumulativeStdNormalProbability(zStatistic);

    inputs_and_statistics.innerHTML= `n1 = ${n_a}<br>p1 = ${p_a}<br>n2 = ${n_b}<br>p2 = ${p_b}<br>Pooled Standard Error (pooled sample variance) = ${pooledStandardError}<br> Z-statistic, ~N(0,1) = ${zStatistic}<br>p-value = ${pValue}<br>`;

    var rejectNullHupothesis = pValue < significanceLevel ? true : false;

    interpret_results.innerHTML=`Since the P-value (${pValue}) is ${ rejectNullHupothesis ? "less" : "greater"} than the significance level (${significanceLevel}), we ${ rejectNullHupothesis ? "reject the Null Hypothesis in favor of the Alternative Hypothesis" : "cannot reject the Null Hypothesis in favor of the Alternative Hypothesis"}.`

    return false;

  function plotSampleData(n_a,p_a,n_b,p_b) {
    var x1 = [];
    var x2 = [];
    var simulationCount = 1000;
    for (var i = 1; i < simulationCount; i++)
      var j_1 = 0, sum_1 = 0;
      while(j_1 < n_a){
        if (Math.random() < p_a) {
          sum_1 += 1;

      var j_2 = 0, sum_2 = 0;
      while(j_2 < n_b){
        if (Math.random() < p_b) {
          sum_2 += 1;

    var trace1 = {
      x: x1,
      name: "Variation A",
      histnorm: "probability density",
      type: "histogram",
      opacity: 0.5,
      marker: {
         color: 'red',
    var trace2 = {
      x: x2,
      name: "Variation B",
      histnorm: "probability density",
      type: "histogram",
      opacity: 0.6,
      marker: {
         color: 'green',

    var data = [trace1, trace2];
    var layout = {
      barmode: "overlay",
      title: "Visualizing the Distributions",
      xaxis: {title: "Success Rate (%)"},
      yaxis: {title: "Frequency Observing This Sample Estimate"}
    Plotly.newPlot('myDiv', data, layout);

    return false;

  // document.onload = plotSampleData(500,0.05,100,0.1);
  document.onload = printFormInputs();