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Sampling Design
But First a Sampling Experiment
Each group of students should:
1. Pull 5 candies out of the bag
2. Weigh the candies
3. Write down the weight
4. Put the candies back in the bag!!
5. Pass the scale and bag to your neighbors
6. Silently multiply the weight of the 5 candies by 20.
Type
Weight (g)
Hersheys
43
Hot tamales
14
Jr mint
18
peanut butter kiss
7
Carmels
8
Discussion
Definitions
•
Sampling
 procedure involving parts of the whole population
•
Sample
 a subset of the pop.
•
Population
 finite group of elements
•
Universe
 infinite group of elements
Why Sample?
•
Pragmatic reasons
 Cheaper
 Easier
 Faster
•
Accurate and reliable results
•
Census?
Sampling
Define the target population
• A sampling frame
•
–Mailing lists
•
Reverse directories
• lists streets and the people that live on them
•
Sampling frame error when the entire population
is not represented in the sampling frame
•
Sampling unit- Single
Random Sampling Error vs.
Nonsampling (Systematic) Error
•
Random Sampling Error
 The difference between the sample results and the results of a census
using the same methods
•
Systematic error
 errors that are not due to chance fluctuations. Sampling frame error is a
systematic error.
Probability vs. Non-probability
sampling
•
Nonprobability- the probability of any particular member of the
population being chosen is unknown.
•
Therefore there are no appropriate statistical techniques for
measuring random sampling error from a nonprobability
sample. Thus making inference is inappropriate.
Non-probability Sampling
•
Convenience Sampling
 do you have a pulse?
Non-probability Sampling
•
Judgment sampling
 using your judgment to select the characteristics of interest
Non-probability Sampling
•
Quota sampling
 a min number of individuals with a certain characteristic.
Non-probability Sampling
•
Snowball sampling
 initial respondents selected with probability methods, and they refer
others
Probability Sampling
•
Simple random sampling –
 everyone in pop has an equal probability of being selected
Probability Sampling
•
Systematic Sampling using every 50th name in a phone book after a random starting point is
selected.
 Sampling interval- in this case 50
 Periodicity- when the names are not ordered randomly
Probability Sampling
•
Stratified sampling (increase homogeniety within strata, increase
heterogeniety between strata)
 Proportional vs. disproportional strata
 Optimal allocation
Probability Sampling
•
Cluster sampling
 Area sample
 Multistage area sampling
Statistics
•
When sampling is not simple random sampling the statistics get
much harder, ie more complex.
•
Observations need to be weighted based upon their probability of
appearing in the sample.
What is the appropriate sample
design?
But First a Sampling Experiment
Each group of students should:
1. Pull 5 candies out of the bag
2. Weigh the candies
3. Write down the weight
4. Put the candies back in the bag!!
5. Pass the scale and bag to your neighbors
6. Silently multiply the weight of the 5 candies by 20.
No Scale
Candy Sample
Type
Nestle Crunch
3 Musketeers
3 Musketeers Mint
Salted Nut Roll
Twizzlers
Starburst
Tootsie Rolls
Milk Duds
Peppermint Patties
Weight (g)
43.9
60.4
35.2
51
14
5
6.66
12
17
No Scale
Candy Sample
Type
Twix
Reese’s “Big Cup”
Gum
Milky Way
Rolo
Weight (g)
56.7
39
5.6
17
6
No Scale
Candy Sample
Type
Crunch
Heath
Milk Duds
3 Muskateers
Hot Tamales
Weight (g)
43.9
14
12
60
14