session 6-8 Flashcards
four types of data
nominal, ordinal, interval, ratio
nominal date is:
Nominal data do not obey any quantitative relationship or any order
ordinal data is:
Ordinal data have categories that represent increasing or decreasing magnitude of a specified attribute but no consistency between values
internval data is:
Interval data have categories that are equally spaced and have true numerical value, but has no true zero
ratio data is:
Ratio data have categories that are equally spaced, have numerical value and a true zero
classification is:
Classification – items sorted into groups which differ in a nominal manner
grading it:
Grading – Methods used in commerce which depend on expert graders
ranking is:
Ranking – Items arranged in order of intensity of a specific attribute
scaling is
Scaling – Items arranged in order by a reference to a scale of numbers
placing a line across a line with not bitter at one end and extremely bitter on the other is considered
scaling
Normal Distribution is
Normal Distribution - mean, median and mode coincide (bell-shaped symmetrical curve)
non-normal distribution is
Non-normal Distribution - mean, median and mode do not coincide (asymmetrical curve)
Descriptive statistic :
Descriptive statistics summarises the data
inferential statistics
Inferential statistics draws conclusions about the population based on a sample
measure of central tendency
Measures of central tendency include mean, median and mode
measure of dispersion
Measures of dispersion include variance, standard deviation and standard error
null hypothesis is
The null hypothesis states that samples are not different (Ho: A = B)
alternative hypothesis is
The alternative hypothesis states that they are different (Ha: A ≠ B)
type 1 error
Type I error - risk of rejecting the null hypothesis when it is true
type 2 error
Type II error - risk of not rejecting the null hypothesis when it is not true
sensory is split into two categories
objective = discrimination, descriptive
Subjective = affective
discrimination is
difference and sensitivity
descriptive is
descriptive analysis and attribute rating
affective is
Qualitative and Quantitative
difference is
overall difference and attribute different( triangle duo-trio, two out of five) and (paired comparison)
sensitivity is
threshold and dilution
category scaling, line scaling, ratio scaling is
attribute
flavour profile, texture profile, quantitative is
descriptive analysis
qualitative is
focus group
quantitative is
acceptance(=hedonic) and preference (=paired comparison and preference ranking)
alpha risk is
α risk - probability of concluding that a difference exists when it does not
beta risk is
β risk - probability of concluding that no difference exists when one does
true or false Discrimination tests are used to determine if a difference or similarity exists between samples
true
pd =
pd – population of distinguishers
