Tests in Sensory Science

Parametric Hypothesis tests are frequently used to measure the quality of sample parameters or to test whether estimates on a given parameter are equal for two samples. Hypothesis tests are parametric tests when they assume the population follows some specific distribution (such as normal) with a set of parameters.
The t-test determines whether a sample is representative of a known population or whether paired samples are likely to be from the same. This test is used for descriptive test in sensory science. Z-Test is preferred under these conditions such as when data points are independent from each other, variance should be same, equal chance of being selected, n is greater then 30 and individual must be randomly selected from population. ANOVA Test is a collection of statistical models used to analyze the differences between group means and their associated procedures. This test is used for difference test in sensory science.
Nonparametric tests, on the other hand, are employed when certain assumptions cannot be made about the population. Rank or ordinal data usually require nonparametric analysis.
Chi-square is useful in sensory research when consumer testing is used to determine whether two distributors (populations) are significantly different.
Friedman test is a non-parametric statistical test. It is used for one-way repeated measures analysis of variance by ranks.

Scientific methodology important to sensory science because according to definition, sensory science is a discipline used to evoke, measure, analyze and interpret those responses to products that are perceived by the senses of sight, smell, touch, taste and hearing. In scientific methodology we have following steps:
Ask a Question Do Background Research  Construct a Hypothesis  Test Your Hypothesis by Doing an Experiment Analyze Your Data and Draw a Conclusion Communicate Your Results These steps are important to sensory science because in sensory