FCP allows group members to describe the product in their own words, which is less structured.

JAR specifically asks team members if a particular product attribute is "just right"

Sample we choose

Sample preparation

Productive information about sample

Presentation of data

Strategy for data

Leader

Background sounds

Ordinal scale rates the data in a specific order, but the intervals between the rates are not equal(involves data that can be ranked or ordered)

Interval scale measures data with equal interval s between values that is data is not only ordered but intervals between the values are equal.

Trained panelists can provide more details and precise information.

2. Size of panel

We need enough panelists to do the test to have enough amount of data.

3. Preparation

Samples should be put into same containers and have 3 digit code. Panelists should not know the detail of the product.

4. Experimental design

The place for testing, the method of giving out the samples and doing the test.

Make sure panelists can not communicate with or see each other.

5. The strategy we use to get the data.

Need to choose an appropriate one from the strategies we know to obtain the data.

6. Leader

We need a leader to tell the panelists what to do and make sure they focus on what they are doing.

7. data analysis

QDA-trained panels

JAR is more quick and easy but the other 2 are time consuming

In JAR it focus on consumers but in QDA and FCP only trained panals and experts are preffered

All 3 are monodic