# Exam statistics The **Exam statistics** page provides a comprehensive view of how your exam is performing across all attempts. It brings together high-level metrics, detailed question analysis and tag-based insights to help you evaluate performance, improve question quality and ensure your assessments are reliable.

Exam statistics is split into 3 different tabs 1. Exam 2. Questions 3. Tags All statistics can be filtered by one or multiple **exam versions**, allowing you to: * Compare different versions of the same exam * Track performance over time * Measure the impact of changes to questions or scoring ## Question Statistics The **Questions** tab provides a detailed breakdown of performance at the individual question level. For each question, you can analyse: * Average score or credits achieved * Distribution of responses * Correct, incorrect and partial answer rates * How candidates interact with answer options

Use the Manage columns drop down to select which columns to have shown or hidden, different question types have different statistics and information available to view

The table below summarises the different columns and what they display. As a quick reminder on credits and points: * **Points** - Are what is awarded for a correct / partially correct response. If negative marking is being used then points are what are deducted for an incorrect answer * **Credits** - The maximum points up for grabs for answering a question correctly

| Column | Description | | ---------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Question stem | A preview of the question as it appeared in the exam (open the toggle to view) | | Average credits | The average number of credits achieved by users in this exam on this question | | Max credits | The maximum number of points that can be awarded for a correct answer | | Partial credits | The number of points awarded for a partially correct answer | | Negative scoring | The number of credits deducted for an incorrect response | | Average score | The average percentage score of the question in this exam | | EMQ | The EMQ group the question belonged to (if any) | | Section | The section ID the question belongs to (if any) | | Subject, Topic, Subtopic, Skill and Difficulty | The faceted tag/s set on the question (if any) | | Total | The total number times the question appeared in completed exam attempts | | Responses |

The number of times the question was answered correct, incorrect, partially correct, or skipped

| | Option breakdown | The number of times each answer option was selected for this question during this exam | | Statistics: Chance | The probability of guessing the correct answer, this is based on the number of possible answers with a single correct answer | | Statistics: P-Value | Item difficulty index ranges from 0 to 1, the higher the p-value the easier the question | | Statistics: Type | The discrimination type will either be the Pearson or Rpb (point biserial). Rpb is a special case of the Pearson's correlation used when the question only has two possible outcomes (correct or incorrect). Pearson will be displayed when there are 15+ responses, and candidates received correct, incorrect, or partial marks, Rpb will be displayed when there are 15+ responses, and candidates received only correct or incorrect marks. | | Statistics: Value | The discrimination index is a measure of the correlation between success in a particular question and success in the entire exam, and ranges from -1 to 1. The higher the value the better the question discrimination between high and low performing candidates. A negative value suggests low performing candidates are more likely to answer the question correctly than high performing candidates. These values will be displayed when there are 15++ responses. | ### Navigating the stats page Search by ID or External ID using the search bar and use the toggle to expand each question in more detail. Questions that require manual marking don't have an aggregated response to show.

{% hint style="info" %} Remember when creating exams, the questions are cloned from the source quiz or quizzes at the time of creation, so any edits you make to questions after the exam has been created won't be pulled through. This means your question stats page could look different to your actual questions if they have been updated. {% endhint %} ### Understanding Questions Statistics Synap provides two key psychometric measures to help evaluate question quality: 1.**Item Difficulty Index** (P-Value) & 2.**Item Discrimination** (Rpb or Pearson Correlation) #### 1.Item Difficulty Index (P-Value) **Formula:** ``` P = Number of Correct Responses ÷ Total Number of Responses ``` **Range:** * `0.00` = No candidates answered correctly (very difficult) * `1.00` = All candidates answered correctly (very easy) **Important Notes:** * P-values are **calculated from actual response data**, not from question settings. * If a P-value is unexpectedly `0.00` or `1.00`, check: * That the correct answer is set in the question editor * That the question has been attempted and marked correctly * Partial credit **does not affect** the P-value — a candidate must receive **full marks** to count as a correct response. #### **2.Item Discrimination (Rpb or Pearson Correlation)** **Definition:**\ Item discrimination measures how well a question **differentiates between high- and low-performing candidates**. In other words: do stronger candidates tend to get this question right? **How it's Calculated in Synap:** * **Point Biserial (Rpb):** Used when a question has only **correct or incorrect outcomes** (i.e. full marks or no marks). * **Pearson Correlation:** Used when a question allows for **partial marks** (e.g. multi-mark, multi-step). **Requirements:** * Discrimination values are only shown when a question has received at least **15 valid responses** to ensure statistical reliability. **Interpretation Guide:** | Discrimination Value | Interpretation | | -------------------- | ------------------------------------------ | | **≥ 0.40** | Very good discrimination | | **0.30 – 0.39** | Good | | **0.20 – 0.29** | Fair | | **< 0.20** | Low — may need review | | **< 0.00** | Negative — likely an issue (e.g. miskeyed) | **Why 15+ Responses?**\ Correlation-based stats (Rpb or Pearson) can be **unstable with small sample sizes**. Fewer than 15 responses can result in misleading values — for example, a single outlier could skew the correlation significantly. > Synap uses a 15-response threshold to ensure that item discrimination values are **statistically meaningful and actionable**. ## Exam statistics The **Exam** tab has an interactive overview of key metrics on your exam, it includes: * Attempt status flow * Score distributions * Version filtering * Highest and lowest average scoring questions * Outcome breakdowns (correct, incorrect, partial, skipped) * Grade breakdowns * Average score by sections

Use the expand (4 arrows) and toggle options (bar or stacked) for different views and more detailed breakdowns of your exams.

#### Exam reliability (KR-20) The **KR-20** statistic measures the internal consistency of the exam — in other words, how reliably the exam assesses the same underlying ability. * A **higher KR-20 score** indicates a more reliable exam * A **lower score** may suggest inconsistent or poorly aligned questions **General guidance:** * ≥ 0.90 — Excellent * 0.80–0.89 — Good * 0.70–0.79 — Acceptable * 0.60–0.69 — Weak * < 0.60 — Poor Reliability becomes more accurate as more attempts are submitted. This metric is particularly useful when reviewing new exams or validating updates to existing ones. ## Tag statistics The **Tags** tab groups performance data based on tags and facets applied to questions. This allows you to analyse results by: * Subject * Topic or subtopic * Skill or competency * Difficulty level Use tag statistics to: * Identify strengths and weaknesses across cohorts * Compare performance across different areas of your content * Ensure balanced coverage across your exam

Learn more about Synap's tag and facet system below {% content-ref url="/pages/2nc56hN8WuQgPO3sSVP7" %} [Facet best practice](/doc/analytics/tags-and-facets/facet-best-practice.md) {% endcontent-ref %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://academy.synap.ac/doc/analytics/exam-statistics.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.