Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Food Analysis > Lecture 2 - Sampling > Flashcards

Lecture 2 - Sampling Flashcards

You may prefer our related Brainscape-certified flashcards:
Gourmet Food flashcards
1
Q

what is sampling? (definition)

A

predetermined procedure for selection, withdrawal, preservation, transportation and preparation of portions to be removed from a lot as samples

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

why do sampling?

A
  • using a fraction of population is faster and cheaper
  • analyzing a whole population is practically difficult
  • gives info about whole population
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

increasing sample size increases…

A
  • accuracy

- also time, cost, sampling methods, logistics of sample handling, analysis and data processing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

appropriate sampling avoids…

A
  1. consumer risk

2. producer’s risk

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

what is consumer risk?

what is producer’s risk?

A

risk of accepting defective product

risk of rejecting an acceptable product

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

what are sampling and non-sampling errors?

A

sampling: arises when sample is not representative of population

non sampling: arises b/c of other reasons (ie environmental error from wrong strage)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

what is variance?

total variance?

A

estimate of uncertainty

total variance: function of sum of variances associated w/ each step

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q
  1. error occuring during sampling?
  2. during sample prep?
  3. during lab analysis?
  4. during data processing?
  5. during interpretation?
A
  1. sampling error
  2. erroneous sample prep
  3. manual or instrumental error
  4. erroneous data handling
  5. erroneous inference
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

factors that affect choice of sampling plans?

A
  1. purpose of inspection
  2. nature of population
  3. nature of product
  4. nature of test method
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

def of sample?

A

portion selected from large quantity of material. (general term)
- diff than lab sample

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

def of lab sample?

A

sample prepared for testing or analysis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

def of population?

A

set of all objects in system being investigated

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

def of lot

A

quantity of bulk material of similar composition whose properties are under study

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

def of batch

A

quantity of food that is known or assumed to be produced under uniform conditions

batch number should always be noted when sampling foods

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

def of unit

A

Each of the discrete, identifiable units of food that are suitable for removal from the population as samples and that can be individually described, analyzed or combined (e.g. an apple, a bunch of bananas, a can of beans, a prepared dish).

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

def of homogeneity

A

degree to which a property or substance is randomly distributed throughout a material.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

def of increment

A

An individual portion of material collected by a single operation of a sampling device.
- Increment can be tested individually or combined and tested as a unit.

18
Q

def of increment

A

An individual portion of material collected by a single operation of a sampling device.
- Increment can be tested individually or combined and tested as a unit.

19
Q

attribute vs variance sampling?

A

attribute:

  • to decide on acceptability of a population based on whether the sample possess a certain characteristic or not
  • 2 possible outcomes (conforming or nonconforming –> present or absent)
  • sample size must be at least ten times smaller than population size

variance

  • estimate quantitatively the amount of substance (ie proteint content or moisture content) or a characteristic (ie color) on a continuous scale
  • esterimate obtained from sample is compared w/ an acceptable value
20
Q

manual vs continuous sampling

A

manual:

  • person doing sampling is trained
  • picks samples randomly from sample lot

continuous:

  • performed mechanically
  • less prone to human bias than manual
21
Q

3 criteria used to determine sample size?

A
  1. level of precision (or sampling error): defines desired level of precision when attributes are measured by using the sample
  2. level of confidence (or risk): 9% confidence level means 95 out of 100 samples have true population value within the range of precision specified
  3. degree of variability among population for attributes being measured: refers to distribution of attributes in population
22
Q

sample size determination can be based on….

A
  1. precision analysis (confidence level)

2. power analysis (power of prediction)

23
Q

Determine the sample size to test the total sugar in a lot of doughnuts with a level of confidence of 95 % and 5% accuracy (precision level). Preliminary test have estimated the average value to be 30 g of sugar per tray. The standard deviation was calculated to be 5g

A

n = ( (1.96 x 5)/(0.05 x 30) )^2

n=43

24
Q

higher standard deviation means what?

A

a more heterogeneous sample

thus the sample size must increase

25
Q

equation for calculating sample size when population size is known?

A

sample size (n) = N / (1+N[e]^2)

n= sample size
N=population size
e=level of precision

26
Q

Q: we have 1000 milk boxes each box contains 6 milk bottles, calculate sample size for 5% accuracy?

A

(n) = N / (1+N(e)^2))

n= 6000 / ( 1+6000[0.05]^2 )

27
Q

sampling plans is classified into…

A
  1. probability sampling plans

2. non probability sampling plans

28
Q

probability sampling plans are classified into… (5)

A
  1. simple random sampling
  2. stratified
  3. cluster
  4. composite
  5. systematic
29
Q

non-probability sampling plans are classified into… (5)

A
  1. judgement sampling
  2. convenience
  3. restricted
  4. quoata
30
Q

what is random sampling?

A
  • each element of population has an equal chance of being included in the samples
  • number of units in the population needs to be known
  • uses a random selection process
31
Q

advantages of random sampling?

A
  1. easy to conduct
  2. high probability of achieving a representative sample
  3. meets assumptions of many statistical procedure
32
Q

disadvantages of random sampling?

A

identification of all units of the population can be difficult

33
Q

what is stratified sampling?

example?

A
  • involves dividing the population into homogeneous subgroups (strata)
  • selecting a simple random sample or another sampling from each stratum

example: eggs are divided into strata: small, medium, large and extra large

34
Q

advantages of stratified sampling?

A
  • homogenous data within each stratum than in the population
  • cost is lower
  • small variances for sample size (higher statistical efficiency)
35
Q

disadvantages of stratified sampling?

A
  • classification error

- prior knowledge of composition and distribution of population

36
Q

what is cluster sampling?

A
  • population is divided into clusters similar to each other

- only some randomly selected clusters are sampled

37
Q

advantages of cluster sampling

disadvantages

A

adv: less costly than simple or stratified
dis: higher sampling error

38
Q

what is composite sampling

A
  • used to obtain samples from bagged products (ie flour, seeds)
  • small portions are taken from different locations, bags or containers and combines in a simple sample
39
Q

what is systematic sampling?

A
  1. first unit is selected at random start from first k population units.
  2. units are taken every nth unit (sample interval).
  3. randomly select number j between 1 and k
  4. the required systematic random sample then comprises units numbered as by: j, j+k, j+2k….j + (n-1)k

N population: units numbered serially from 1 to N

sample size n = drawn from N

k = sampling interval

k = N/n

40
Q

advantages of systematic sampling?

A

easy to perform

less subject to error

provides greater info per unit cost

41
Q

what is probability sampling

A

selection of a sample from a population based on chance

probability of inclusion and sampling errors are known

42
Q

what is the equation for calculating sample size according to precision analysis?

A

n = [ ((z) * (SD)) / (y * x) ]^2

n= sample size
z=z value according to level of confidence
SD=standard deviation
Y = accuracy
x = population mean

Food Analysis (17 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions