physics

Discrimination testing

Discrimination testing is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Discrimination testing rather than just read about it. In short: Discrimination testing is a technique employed in sensory analysis to determine whether there is a detectable difference among two or more products. The test uses a group of assessors (panellists) with a degree of training appropriate to the complexity of the test to discriminate from one product to another through one of a variety of experimental designs.

Key takeaways

Discrimination testing belongs to physics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Discrimination testing to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Discrimination testing from memory before moving on to harder problems.

Reference excerpt

Discrimination testing is a technique employed in sensory analysis to determine whether there is a detectable difference among two or more products. The test uses a group of assessors (panellists) with a degree of training appropriate to the complexity of the test to discriminate from one product to another through one of a variety of experimental designs. Though useful, these tests typically do not quantify or describe any differences, requiring a more specifically trained panel under different study design to describe differences and assess significance of the difference.

Statistical basis The statistical principle behind any discrimination test should be to reject a null hypothesis (H0) that states there is no detectable difference between two (or more) products. If there is sufficient evidence to reject H0 in favor of the alternative hypothesis, HA: There is a detectable difference, then a difference can be recorded. However, failure to reject H0 should not be assumed to be sufficient evidence to accept it. H0 is formulated on the premise that all of the assessors guessed when they made their response. The statistical test chosen should give a probability value that the result was arrived at through pure guesswork. If this probability is sufficiently low (usually below 0.05 or 5%) then H0 can be rejected in favor of HA. Tests used to decide whether or not to reject H0 include binomial, χ2 (Chi-squared), t-test etc.

Types of test

A number of tests can be classified as discrimination tests. If it's designed to detect a difference then it's a discrimination test. The type of test determines the number of samples presented to each member of the panel and also the question(s) they are asked to respond to. Schematically, these tests may be described as follows; A & B are used for knowns, X and Y are used for different unknowns, while (AB) means that the order of presentation is unknown:

Paired comparison XY or (AB) – two unknown samples, known to be different, test is which satisfies some criterion (X or Y); unlike the others this is not an equality test. Duo-trio AXY – one known, two unknown, test is which unknown is the known (X = A or Y = A) Triangle (XXY) – three unknowns, test is which is odd one out (Y = 1, Y = 2, or Y = 3). ABX ABX – two knowns, one unknown, test is which of the knowns the unknown is (X = A or X = B). Duo-trio in constant reference mode (AB)X – three unknowns, where it is stated that the first two are different, but which is which is not identified, test is which of the first two the third is (X = 1 or X = 2). Tetrad (XXYY) - four unknowns, test is to create groups of size two based on similarity (XX = (1,2), XX = (1,3) or XX = (1,4)). Like the triangle test, this technique has a 1/3 probability that a random guess is correct. However, the tetrad test in some cases requires only one third the number of overall participants to establish statistical significance compared to the triangle test.

Worked examples

Example 1 — a first encounter with Discrimination testing

Start with the simplest possible case. Write down what Discrimination testing claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Discrimination testing before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Discrimination testing ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Discrimination testing

In research: Discrimination testing appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Discrimination testing in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Discrimination testing is common in secondary-school and first-year university syllabi. It links to neighbouring topics Nonverbal communication, Product testing, Psychophysics, so understanding it makes those chapters shorter.
In everyday life: Look for Discrimination testing outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Discrimination testing in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Discrimination testing means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Discrimination testing out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Discrimination testing in simple terms?

Why does Discrimination testing matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Discrimination testing?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Discrimination testing.