Extended Project Qualification (EPQ) Analysis, Argument and Critical Thinking Syllabus

What is thematic analysis in qualitative research?

Thematic analysis is a method of identifying, coding, and interpreting recurring patterns (themes) within qualitative data such as interviews or texts to draw meaningful conclusions about the subject.

What is 'coding' in qualitative data analysis?

Coding is the process of labelling segments of qualitative data with tags or categories so that recurring ideas can be grouped, compared, and developed into broader themes.

What is quantitative data?

Quantitative data is numerical information that can be measured and counted, such as test scores, frequencies, percentages, and measurements, allowing statistical analysis and comparison.

Distinguish between discrete and continuous quantitative data.

Discrete data takes separate, countable values (e.g. number of students). Continuous data can take any value within a range and is measured (e.g. height, time, temperature).

Define the mean, median, and mode as measures of central tendency.

The mean is the arithmetic average $\bar{x} = \frac{\sum x}{n}$. The median is the middle value when data are ordered. The mode is the most frequently occurring value.

How do you calculate the range of a data set, and what does it measure?

The range is $\text{range} = x_{\max} - x_{\min}$, the difference between the largest and smallest values. It measures the spread (dispersion) of the data but is sensitive to outliers.

What does the standard deviation measure, and what is its formula?

Standard deviation measures the average spread of values around the mean. For a population: $\sigma = \sqrt{\frac{\sum (x - \mu)^{2}}{n}}$. A larger value indicates greater dispersion.

What is the difference between a population and a sample?

A population is the entire group being studied; a sample is a smaller subset selected from that population. Samples are used to make inferences about the population when studying everyone is impractical.

What is the difference between correlation and causation?

Correlation means two variables vary together (a statistical association), whereas causation means one variable directly produces a change in the other. Correlation does not, by itself, prove causation.

What does a correlation coefficient $r$ indicate, and what is its range?

The correlation coefficient $r$ measures the strength and direction of a linear relationship between two variables. It ranges from $-1$ (perfect negative) through $0$ (no linear relationship) to $+1$ (perfect positive).

When should you use a bar chart versus a histogram?

A bar chart displays categorical (discrete) data with gaps between bars. A histogram displays continuous data grouped into intervals with bars touching, showing the distribution of a frequency.

What type of data is a pie chart best suited to displaying?

A pie chart is best for showing proportions or percentages of a whole for categorical data, where each segment represents a category's share of the total (summing to 100%).

When is a line graph the most appropriate way to present data?

A line graph is best for showing trends or changes in a continuous variable over time or showing the relationship between two continuous variables.

What is a scatter graph used to display?

A scatter graph plots paired values of two variables as points to reveal the relationship or correlation between them, including its strength, direction, and any outliers.

List three principles of presenting data visually with integrity.

Use clear titles and labelled axes with units; start axes appropriately (avoid misleading truncated scales); choose the chart type that suits the data; and avoid distorting or cherry-picking to mislead.

How can a graph mislead through its axis scale?

Truncating the y-axis so it does not start at zero, or using uneven/compressed scales, exaggerates or minimises differences, making changes appear larger or smaller than they truly are.

What does it mean to acknowledge the limitations of your data?

It means openly identifying weaknesses such as small sample size, bias, lack of representativeness, measurement error, or limited scope, that restrict how confidently conclusions can be drawn.

What is sampling bias and why does it matter?

Sampling bias occurs when the sample is not representative of the population, so certain groups are over- or under-represented. It matters because it distorts results and limits the validity of generalisations.

What is the difference between reliability and validity in data?

Reliability is the consistency of results when a measurement is repeated. Validity is whether the data actually measures what it claims to measure. Data can be reliable yet invalid.

What criteria can you use to evaluate the strength of a piece of evidence?

Consider its source credibility and expertise, relevance to the claim, recency (currency), sample size, objectivity (absence of bias), reproducibility, and whether it is corroborated by other independent sources.

What is the difference between a primary and a secondary source?

A primary source is original first-hand material or data (e.g. your own survey, original documents). A secondary source interprets, analyses, or summarises primary sources (e.g. textbooks, review articles).

What is the difference between empirical evidence and anecdotal evidence?

Empirical evidence is gathered through systematic observation, measurement, or experiment and is generalisable. Anecdotal evidence is based on isolated personal accounts and is unreliable for drawing broad conclusions.

What does it mean to weigh different viewpoints objectively?

It means evaluating each perspective fairly on the merit of its evidence and reasoning, setting aside personal bias, giving due weight to opposing views, and judging which is best supported rather than which you prefer.

What is confirmation bias, and how does it threaten objective analysis?

Confirmation bias is the tendency to seek, favour, and remember information that supports your existing beliefs while ignoring contradictory evidence. It undermines objectivity by skewing analysis toward a predetermined conclusion.

What is an assumption in the context of an argument?

An assumption is an unstated belief or premise taken for granted as true, which an argument relies on to work. If the assumption is false, the argument may collapse.

How do you identify the assumptions underlying an argument?

Ask what must be true for the reasons to support the conclusion, look for unstated gaps between premise and claim, and question values, definitions, or causal links the author treats as obvious.

What is the difference between a fact, an opinion, and a value judgement?

A fact is verifiable and can be proven true or false. An opinion is a personal belief or interpretation. A value judgement evaluates something as good/bad or right/wrong based on standards or values.

What does it mean to form an independent, reasoned judgement in an EPQ?

It means reaching your own conclusion grounded in your critical evaluation of evidence and arguments, rather than simply repeating others' views, while justifying it with sound reasoning and acknowledging its limits.

Why is triangulation valuable when reaching a conclusion?

Triangulation uses multiple sources, methods, or types of data to investigate the same question. Convergent findings increase confidence and validity, while divergence highlights where caution or further inquiry is needed.

What is the difference between objectivity and subjectivity in analysis?

Objectivity is judgement based on observable evidence and reasoning, independent of personal feelings. Subjectivity is shaped by personal opinions, emotions, or bias. Critical analysis strives for objectivity while recognising unavoidable subjectivity.