## Random sample

### Random Sampling

In the spheres of statistics and research, a random sample denotes a subset of individuals derived from a broader population. The distinctive trait of random sampling resides in the equal opportunity for each population member to be included in the sample. This technique plays a pivotal role in bias reduction and ensuring the sample's representativeness of the total population, thereby augmenting the validity and applicability of the research outcomes.

### Types of Random Sampling

There exist diverse methods of random sampling, including:
Simple Random Sampling: In this approach, each population member stands an equal opportunity of selection, and the sampling procedure is performed without replacement.
Systematic Random Sampling: In this method, researchers opt for every nth population member, with n being a constant interval.
Stratified Random Sampling: In this technique, the population is segmented into strata or groups based on specific attributes, following which a random sample is extracted from each group.
Cluster Random Sampling: This approach involves dividing the population into clusters or groups, post which a random selection of clusters is chosen for in-depth analysis.

### Advantages and Disadvantages of Random Sampling

Reduced Bias: Random sampling reduces the potential for bias, ensuring the sample's representativeness of the larger population.
Generalizability: Conclusions drawn from a random sample can be extrapolated to the broader population with greater assurance.

Resource Intensive: Random sampling might be time and resource-intensive, especially when addressing large populations.
Infeasibility: In some instances, creating a sampling frame that encompasses every population member may prove challenging or unfeasible.

### Applications of Random Sampling

Random sampling is extensively employed across various fields:
Social Sciences: Social scientists harness random sampling to investigate human behavior, attitudes, and opinions in a manner representative of the population.
Market Research: Business enterprises utilize random sampling to collate consumer feedback, ensuring that the sample embodies the target market.
Public Health: Health researchers leverage random sampling to ascertain the prevalence of diseases, health-related behaviors, and risk factors within a population.
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