MDM_samp_simple

Yook, Chen, Armen

**Simple random sampling **  Simple random sampling (SRS) happens when each unit (n) of population (N) has an equal probability of composing the sample. The characteristics are unbiased and independent which means they do not affect the chance of others being selected. When it comes to picking a sample, all specific characteristics (i.e. gender, age, etc) are not considered as factors. This gives any of the possible candidates in the population an equal chance of being picked.

To conduct a simple random sampling, members of the population have to be numbered and then some of the numbered members are selected either with or without a mechanical device.

There are two types of simple random sampling: __Simple Random Sampling with Replacement__ and __Simple Random Sampling without Replacement.__   __Simple Random Sampling with Replacement: __  __Simple Random ____Sampling without Replacement: __ 
 * This type of sampling occurs when a single member is chosen from a population of candidates and then put back into that population. A member of the population can be selected more than once.
 * This means that no matter how many people ore chosen, the probability of anyone (even the ones that were already sampled) being chosen remains the same the whole way through.
 * This type of sampling almost follows the principles of simple random sampling with replacement.
 * The only difference is that when the single member is taken from the population, the member is not put back into that population. A member of the population cannot be selected more than once.
 * This means that for every person who is chosen, the probability for the next set of possible candidates to be chosen changes and the probabily of one being included in the sample is no longer independent.

<span style="color: #444444; font-family: 'Tahoma','sans-serif'; font-size: 10pt;">Simple random sampling without replacement is used more frequently used than simple random sampling with replacement because it gives more precision than sampling with replacement. <span style="font-family: Tahoma,Geneva,sans-serif;"> <span style="font-family: Tahoma,Geneva,sans-serif;">Simple random sampling is simplest method of sampling and it is fair. However with a bad luck, the sample selected by this method may be inefficient to represent the population. In order to make simple random sampling efficient, a large sample is required. <span style="color: #444444; font-family: 'Tahoma','sans-serif'; font-size: 10pt;">Simple random sampling is easy and cheap when surveying a small population, but it is expensive when surveying a large population. For this reason, simple random sampling is rarely used and other methods of samplig are often required.


 * <span style="color: #444444; font-family: 'Tahoma','sans-serif'; font-size: 10pt;">Example **<span style="color: #444444; font-family: 'Tahoma','sans-serif'; font-size: 10pt;">:Lottery

It does not matter what number you are choosing, each combination of six numbers all have the same chances to be selected. People usually ignore simple number such as 6-5-4-3-2-1 but it actually has the exactly same probability of winning as 52-41-39-13-12-3 does.

**<span style="color: #444444; font-family: 'Tahoma','sans-serif'; font-size: 10pt;">Bibliography ** <span style="color: #444444; font-family: 'Tahoma','sans-serif'; font-size: 10pt;">

//<span style="font-family: 'Tahoma','sans-serif'; mso-bidi-font-size: 10.0pt; mso-font-kerning: 0pt;">Learning Resources: Statistics: Power from Data! Probability sampling //<span style="font-family: 'Tahoma','sans-serif'; mso-bidi-font-size: 10.0pt; mso-font-kerning: 0pt;">. (2009, April 20). Retrieved October 22, 2009, from http://www.statcan.gc.ca/edu/power-pouvoir/ch13/prob/5214899-eng.htm

//<span style="font-family: 'Tahoma','sans-serif'; mso-bidi-font-size: 10.0pt; mso-font-kerning: 0pt;">Simple Random Sampling //<span style="font-family: 'Tahoma','sans-serif'; mso-bidi-font-size: 10.0pt; mso-font-kerning: 0pt;">. (n.d.). Retrieved October 22, 2009, from http://www.emathzone.com/tutorials/basic-statistics/simple-random-sampling.html

Trochim, W. M. (2006, October 20). //Probability Sampling//. Retrieved October 25, 2009, from http://www.socialresearchmethods.net/kb/sampprob.php

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