Types of Sampling Plans, Study notes of Statistics

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TYPES OF SAMPLING PLANS

CHEM 251 SDSU

Let’s use the table to pick 10 random numbers between 1 and 50. To do so, we choose a random s perhaps by dropping a pencil onto the table. For this exercise, we will assume that the starting po row of the third column, or 12032. Because the numbers must be between 1 and 50, we will us digits, ignoring all two-digit numbers less than 01 or greater than 50, and rejecting any duplicate down the third column, and moving to the top of the fourth column when necessary, gives the random numbers: 32, 01, 05, 16, 15, 38, 24, 10, 26, 14. These random numbers (1000 total digits) are a small subset of values from the publication Mi Digits (Rand Corporation, 2001) are are used with permission. Information about the publication a text file containing the million random digits is available at http://www.rand.org/pubs/monogr MR1418/. 11164 36318 75061 37674 26320 75100 10431 20418 19228 21215 91791 76831 58678 87054 31687 93205 43685 19732 10438 44482 66558 37649 08882 90870 12462 41810 01806 36792 26236 33266 66583 60881 97395 20461 36742 02852 73944 04773 12032 51414 82384 38370 00249 80709 72605 49563 12872 14063 93104 78483 72717 68714 18048 25005 64208 48237 41701 73117 33242 42314 83049 21933 92813 51486 72875 38605 29341 80749 80151 33835 52602 79147 99756 26360 64516 17971 48478 09610 04638 17141 09227 71325 55217 13015 72907 00431 45117 33827 92873 02953 65285 97198 12138 53010 95601 15838 16805 61004 43516 17264 57327 38224 29301 31381 38109 34976 65692 98566 95639 99754 31199 92558 68368 04985 51092 37780 40261 61555 76404 86210 11808 12841 45147 97438 60022 12645 78137 98768 04689 87130 79225 08153 84967 64539 79493 62490 99215 84987 28759 19177 14733 24550 28067 68894 24216 63444 21283 07044 92729 37284 13211 37485 10415 16975 95428 33226 55903 31605 43817 22250 03918 46999 59138 39542 71168 57609 91510 77904 74244 50940 31553 29478 59652 50414 31966 87912 87514 12944 49862 96566

RANDOM SAMPLING

• (^) Random sampling consists of an

unbiassed selection of samples from

the population (difficult to do in

reality).

• Approach:
  • (^) Segment sample into grid of

batches.

• (^) Use a random number table

(generator) to select coordinates.

Random Number Table

we sample the target population at regular intervals in space or t

7.3 shows an aerial photo of the Great Salt Lake in Utah. A ra

divides the lake into two sections with different chemical compo

compare the lake’s two sections—and to evaluation spatial variat

each section—we use a two-dimensional grid to define samplin

4 Borgman, L. E.; Quimby, W. F. in Keith, L. H., ed. Principles of Environmental Sa can Chemical Society: Washington, D. C., 1988, 25–43.

Fig

take

of a

lake

tion

sect

the

cou

NA

E-

railroad line

SYSTEMATIC SAMPLING

• Systematic sampling is

performed by dividing

the target population into

regular intervals of space

or time.

• The sampling is then

performed equally within

each of these intervals.

we sample the target population at regular intervals in space or t

7.3 shows an aerial photo of the Great Salt Lake in Utah. A ra

divides the lake into two sections with different chemical compo

compare the lake’s two sections—and to evaluation spatial variat

each section—we use a two-dimensional grid to define samplin

4 Borgman, L. E.; Quimby, W. F. in Keith, L. H., ed. Principles of Environmental Sa can Chemical Society: Washington, D. C., 1988, 25–43.

Fig

take

of a

lake

tion

sect

the

cou

NA

E-

railroad line

SYSTEMATIC -JUDGEMENTAL

SAMPLING

• Systematic-Judgmental

sampling uses prior

knowledge to guide the

systematic sampling.

• If we know that a pollutant

of interest is in the lake

north of the railroad line,

there is no point sampling

south of the line.