Random sampling or probability sampling refers to the sampling technique in which each sample has an equal chance of being chosen. Samples chosen randomly are supposed to be an unbiased representation of a statistical population. This method is the easiest among all probability sampling techniques. It involves random selection and requires little prior knowledge about the population. There are different techniques for selecting a random sample. This article will tell you about the top procedures for selecting a random sample.

**Description Of Random Sampling**

The random sampling method is one of the most common and easiest methods for selecting a random sample. Researchers use this method to collect objective data. The random sampling method assumes that the chosen sample is representative of the entire population. It helps the researchers collect unbiased data, which leads to valid and accurate results.

Researchers can use random sampling to draw statistical inferences about a population. It helps researchers in maintain the internal validity of the results. Randomisation is the best approach for reducing the interference of external variables. Furthermore, random sampling allows for the selection of a large sample size which increases the external validity of the sample. It indicates the overall attributes and features of the entire population.

**Types of Random Sampling**

There are four types of random sampling techniques that you can use for selecting a random sample.

**Simple Random Sampling**

Simple random sampling entails using random numbers to choose a random sample. Selecting a random sample requires meeting the following criteria:

- You have the data on every member of the population
- It is easier to contact and access the population members once selected
- Availability of funds and ample time for collecting data from the sample size

If you are writing a stat dissertation and using simple random sampling, you can hire best dissertation writing services if you are facing any issues.

**Stratified Random Sampling**

Using stratified random sampling for selecting a random sample requires dividing the population into groups based on common characteristics. After dividing the population into groups, you can choose a random sample. This method is useful for the equitable inclusion of different population segments.

**Cluster Random Sampling**

Cluster random sampling is useful when it is impossible to sample from the overall population. You can divide the sample into clusters that roughly represent the entire population. In the next step, you can choose your sample randomly from a subset of these clusters.

**Systematic Random Sampling**

You can use a systematic random sampling technique to choose the sample members from a wider population using a defined periodic interval but a random beginning point.

**What Are The Steps For Selecting A Random Sample?**

Here are the steps you can take for selecting a random sample:

**Step 1: Define the Population**

Selecting a random sample entail defining the population. The first step is to define the population you want to study. You must define the sampling frame you want to utilise for data collection and analysis. For example, suppose you want to study the university students. In that case, your frame of reference will be both male and female students, as denoted by N. However, if your frame of reference is male students, you will have to exclude the female students. It is essential to ensure that you have complete data about every member of the statistical population.

**Step 2: Choose Your Sample Size**

The next step in selecting a random sample is deciding the sample size. Large sample sizes have more statistical power but are costly and time-consuming. You can choose a sample size by implementing the following techniques:

- Define the confidence intervals and confidence level. In statistics, a confidence interval describes the likelihood that a population parameter would lie between a range of values for a given percentage of the time. Confidence level indicates the occurrence of an estimate between the upper and lower range of confidence interval. Standard confidence intervals and levels are between 0.05 and 0.95.
- You can also use a sample size calculator for choosing the sample size of a random sample. You can insert the values of population size and set the confidence level. Once you insert the values, the sample size calculator will provide you with the ideal sample size and margin of error.

**Step 3: Random Selection of the Sample**

The next step for selecting a random sample entails the employment of the following procedures:

**Lottery Method**

The lottery system is one of the traditional methods and a mechanical illustration of random sampling. In this approach, the researcher assigns a number to each person in the population. To select samples, researchers randomly select numbers from a container. You can also use computer programs to simulate the lottery system.

**Random Number Method**

You can also use the random number method for selecting a random sample. This technique requires numbering each individual. You can use a random number generator or random number tables for randomly selecting the sample. You can also list population members with their assigned numbers in the Excel sheet and use the RAND function to assign random numbers.

**Advantages Of Random Sampling Technique**

- It is an impartial type of sampling method, and when used properly, it aids in minimising bias compared to other sampling methods.
- It is typically simple to choose a smaller sample size from the higher population density because it requires a large sample frame.
- The researcher need not be familiar with the information they are gathering beforehand. Subject matter expertise is not necessary.
- A crucial technique for gathering the data is the random sampling approach. Technical expertise is not a prerequisite. You only need the basic skills of recording and listening abilities.
- The more samples you choose, the higher the quality of the data collection will be using the random sampling technique.

**Conclusion**

Researchers must ensure that every randomly selected individual participates in the study. It ensures the validity of the research findings. The rationale for selecting a random sample is to reduce biasness and devise a representative sample of the entire population. If some of the chosen members do not participate in the study, it can affect the research findings. So, it is important to ensure that every member participates in the study. You can follow the above-mentioned guidelines to select a random sample.