The statistical sample is a metric that allows for a general overview of the population.
Therefore, it represents the opinion of several people.
The statistical sample enables us to investigate certain characteristics and preferences of the target audience during market research.
Types of Statistical Samples
The statistical sample is divided into two types: random or stratified.
Random Sample
A random sample consists in selecting individuals through random processes.
In this way, every member of the population has an equal chance of being chosen to represent the sample.
This method is very costly but more effective
.Moreover, in some cases, it can be a slow and complex process.
The choice of the sample in random sampling is left to chance and should not be influenced by the researcher conducting the survey.
To perform such sampling it is important to number all units of the population, put into an urn as many numbered balls as there are units in the population, all identical to each other, and then draw from that urn the balls to form the sample.
Stratified Sample
The stratified sample, on the other hand, is drawn by dividing the population into homogeneous subgroups based on selected characteristics.
This works as follows: once the population is divided into subgroups called "strata", the one that is most homogeneous for the survey is chosen for sampling.
Subsequently, samples are drawn for each stratum through a random sampling procedure.
Finally, the two samples are combined, resulting in the global sample.
Statistical Sampling Formula
We consider the population and its binomial coefficient.
If it corresponds to the number of combinations without repetition where n are the elements drawn from a group of N≥n units.
Each unit of the population is associated with a probability of being included in the sample.
This is equal to the sum of the probabilities of drawing all the c's, or the samples.
Simple Random Sampling Without Replacement
The simple random sampling without replacement refers to each unit having a probability n/N of belonging to the sample.
It is important to process the statistics on the total intercepted to indicate how large it actually is compared to the target potential.
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