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examBoard: AQA
examType: GCSE
lessonTitle: Frequency Tables and Diagrams
Psychologists collect loads of data in their research, but all those numbers would be meaningless without proper organisation. That's where frequency tables and diagrams come in! They help researchers make sense of their findings and spot patterns that might otherwise stay hidden.
Key Definitions:
Imagine trying to spot patterns in hundreds of numbers written in a list! Our brains aren't wired to process raw data efficiently. Visualisations transform complex information into formats our visual system can quickly understand, helping us to:
In psychology, we study human behaviour and mental processes, which can be tricky to measure. Good data handling helps psychologists:
A frequency table is the starting point for organising data. It shows how many times each value or category appears in your dataset. Let's look at how to create and use them.
Imagine a psychologist has asked 30 students to rate their anxiety before an exam on a scale of 1-5 (where 1 is very calm and 5 is very anxious). Here's how to organise this data:
| Anxiety Rating | Tally | Frequency |
|---|---|---|
| 1 (Very calm) | IIII | 4 |
| 2 (Calm) | IIII II | 7 |
| 3 (Neutral) | IIII III | 8 |
| 4 (Anxious) | IIII I | 6 |
| 5 (Very anxious) | IIIII | 5 |
| Total | 30 |
This simple table already tells us something interesting - most students reported moderate anxiety (rating of 3), with fewer at the extremes.
Sometimes we have data with many different values. Grouping them makes the data easier to handle. For example, if we measured reaction times (in milliseconds) for 50 participants in a psychology experiment:
| Reaction Time (ms) | Frequency |
|---|---|
| 200-249 | 7 |
| 250-299 | 12 |
| 300-349 | 16 |
| 350-399 | 10 |
| 400-449 | 5 |
| Total | 50 |
Once we have our frequency tables, we can transform this data into visual formats that make patterns easier to spot. Let's explore the most common types used in psychology.
Perfect for showing categorical data (like different treatment groups or survey responses). Each bar represents a category and its height shows the frequency.
When to use: Comparing different groups or categories
Example: Comparing therapy outcomes across different age groups
Similar to bar charts but used for continuous data. The bars touch each other to show the continuous nature of the data.
When to use: Showing the distribution of continuous data like test scores or reaction times
Example: Distribution of IQ scores in a population
Shows how a whole is divided into parts. Each slice represents a proportion of the total.
When to use: Showing proportions or percentages of a whole
Example: Breakdown of different diagnoses in a mental health clinic
Let's use our anxiety ratings example to create a bar chart:
The bar chart shows that most students reported moderate anxiety (rating of 3).
A good bar chart should always include:
In 1854, London faced a severe cholera outbreak. Dr. John Snow suspected contaminated water was the cause, but couldn't prove it with just numbers. He created a map showing cholera deaths as dots, which clustered around a specific water pump on Broad Street. This visual evidence convinced authorities to remove the pump handle, helping end the epidemic.
This historical example shows how visualising data can reveal patterns that raw numbers hide. In psychology, the same principle applies - visualisations help us see connections between mental processes, behaviours and treatments that might otherwise remain invisible.
Frequency tables aren't just for creating graphs - they help us calculate important statistical measures too.
To find the mean (average) from a frequency table:
Using our anxiety ratings example:
| Anxiety Rating (x) | Frequency (f) | x × f |
|---|---|---|
| 1 | 4 | 4 |
| 2 | 7 | 14 |
| 3 | 8 | 24 |
| 4 | 6 | 24 |
| 5 | 5 | 25 |
| Total | 30 | 91 |
Mean = Sum of (x × f) ÷ Total frequency = 91 ÷ 30 = 3.03
So the average anxiety rating is approximately 3.03, which tells us the typical student feels moderate anxiety before exams.
The mode is the easiest to find - it's simply the value with the highest frequency. In our anxiety example, the mode is 3 (with 8 students).
For the median (the middle value when data is arranged in order), we need to find the (n+1)÷2 position where n is the total frequency. With 30 students, we need the (30+1)÷2 = 15.5 position, which means the average of the 15th and 16th values when arranged in order.
Different types of data call for different visualisations. Here's a quick guide:
One of the most famous data visualisations in psychology is the normal distribution or "bell curve." Many psychological traits (like IQ, personality traits and reaction times) follow this pattern when measured in large populations.
Psychologists use histograms to check if their data follows this pattern. If it does, they can use powerful statistical tools to analyse it. This is why proper data handling and visualisation are essential skills for psychological research.
Frequency tables and diagrams aren't just boring maths - they're essential tools that help psychologists:
By mastering these skills, you're learning to think like a real psychologist - looking beyond individual cases to find patterns that help us understand the human mind.
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