Simple random sampling is a method used to cull a smaller sample size from a larger population and use it to research and make generalizations about the larger group. It is one of several methods statisticians and researchers use to extract a sample from a larger population; other methods include stratified random sampling and probability sampling. The advantages of a simple random sample include its ease of use and its accurate representation of the larger population.
How a Simple Random Sample Is Generated
Researchers generate a simple random sample by obtaining an exhaustive list of a larger population and then selecting, at random, a certain number of individuals to comprise the sample. With a simple random sample, every member of the larger population has an equal chance of being selected.
Researchers have two ways to generate a simple random sample. One is a manual lottery method. Each member of the larger population group is assigned a number. Next, numbers are drawn at random to comprise the sample group. if a simple random sample were to be taken of 100 students in a high school with a population of 1,000, then every student should have a one in 10 chance of being selected.
The manual lottery method works well for smaller populations, but it isn't feasible for larger ones. In these situations, researchers prefer computergenerated selection. It works via the same principle, but a sophisticated computer system, rather than a human being, assigns numbers and selects them at random.
Room for Error
With a simple random sample, there has to be room for error represented by a plus and minus variance. For example, if in that same high school a survey were to be taken to determine how many students are lefthanded, a random sampling can determine that eight out of the 100 sampled are lefthanded. The conclusion would be that 8% of the student population of the high school are lefthanded, when in fact the global average would be closer to 10%.
The same is true regardless of subject matter. A survey on the percentage of the student population that has green eyes or is physically incapacitated would result in a high mathematical probability based on a simple random survey, but always with a plus or minus variance. The only way to have a 100% accuracy rate would be to survey all 1,000 students which, while possible, would be impractical. (For related reading, see: What percentage of the population do you need in a representative sample?)
Advantages of Random Sampling
Simple random sample advantages include ease of use and accuracy of representation. No easier method exists to extract a research sample from a larger population than simple random sampling. There is no need to divide the population into subpopulations or take any steps further than plucking the number of research subjects needed at random from the larger group. Again, the only requirements are that randomness governs the selection process and that each member of the larger population has an equal probability of selection.
Selecting subjects completely at random from the larger population also yields a sample that is representative of the group being studied. Even sample sizes as small as 40 can exhibit low sampling error when simple random sampling is performed correctly. For any type of research on a population, using a representative sample to make inferences and generalizations about the larger group is critical; a biased sample can lead to incorrect conclusions being drawn about the larger population.
Simple random sampling is as simple as its name indicates, and it is accurate. These two characteristics give simple random sampling a strong advantage over other sampling methods when conducting research on a larger population.
(For related reading, see: What are the disadvantages of using a simple random sample to approximate a larger population?)

What are the disadvantages of using a simple random sample to approximate a larger ...
Learn what a simple random sample is, how researchers use it as a statistical tool and the disadvantages it carries when ... Read Answer >> 
What's an example of stratified random sampling?
Stratified random sampling divides a population into subgroups or strata, whereby the members in each of the stratum formed ... Read Answer >> 
What percentage of the population do you need in a representative sample?
Learn about representative samples and how they are used in conjunction with other strategies to create useful data with ... Read Answer >> 
What are the advantages and disadvantages of using systematic sampling?
Learn about the primary advantages and disadvantages of using a systematic sampling method when conducting research of a ... Read Answer >> 
What is the difference between the standard error of means and standard deviation?
Learn about the difference between the standard error of the mean and the standard deviation and how standard deviation is ... Read Answer >> 
What is a relative standard error?
Find out how to distinguish between mean, standard deviation, standard error and relative standard error in statistical survey ... Read Answer >>

Investing
Find the right fit with probability distributions
Discover a few of the most popular probability distributions and how to calculate them. 
Insights
These Companies Are Poised for Growth as Global Population Growth Comes Online
While there are many concerns about population growth putting pressure on natural resources such as water and energy, these increased demands can spell profits for certain companies that can ... 
Financial Advisor
5 Powerful Website Tools Every Advisor Needs
Topperforming financial advisor websites have these five features in common. 
Insights
4 Global Economic Issues of an Aging Population
Discover why dramatic increases in life expectancy is creating significant socioeconomic challenges for many advanced industrialized nations. 
Tech
New Advances In AI From Google Acquisition DeepMind (GOOG, AAPL)
DeepMind's texttospeech system can reproduce human speech patterns and produce music. 
Retirement
SIMPLE IRA Plans: Are They Really Simple?
Contrary to what their name implies, SIMPLE IRA plans aren't always simple for an employer. 
Insights
How Demographics Drive The Economy
Demographics can have a profound effect on the economy. An aging population coupled with a declining birthrate points to a decline in economic growth. 
Insights
What China's New Policy Means for Business
Now that China has eliminated its onechild policy, how will the new policy impact businesses? 
Investing
Elements of Insurable Risks: A Quick Guide
Explore the elements of insurable risk: due to chance, measurable and definite, predictability, noncatastrophic, random selection and large loss exposure.

Sample
A sample is a smaller, manageable version of a larger group. ... 
Sampling
Sampling is a process used in statistical analysis in which a ... 
Representative Sample
Representative Sample is a subset of a statistical population ... 
Random Factor Analysis
Random factor analysis is a statistical technique to decipher ... 
Standard Error
Standard error is the standard deviation of a sample population. 
T Distribution
A T distribution is a type of probability function that is appropriate ...