A Sample Investigation is the process of learning about the population based on a sample that you draw from it. In this technique, instead of using all items in a universe, you use only a part of the universe for study. Also, you draw conclusions based on the sample for the entire universe. Let’s look at the objectives, essentials, merits, and demerits of a sample investigation.
Suggested Videos
Objectives of a Sample Investigation
The primary objectives of collecting and analyzing a sample investigation are to reveal characteristics of a population as follows:
- Estimating the parameters of the population like means, median, mode, etc.
- Testing validity statements about the population
- Investigating the changes in population over time
In other words, the sampling process involves three main elements – selecting the sample, collecting the information, and also making inferences about the population.
Browse more Topics under Descriptive Statistics
- Definition and Characteristics of Statistics
- Stages of Statistical Enquiry
- Importance and Functions of Statistics
- Nature of Statistics – Science or Art?
- Application of Statistics
- Law of Statistics and Distrust of Statistics
- Meaning and Types of Data
- Methods of Collecting Data
- Census
- Classification of Data
- Tabulation of Data
- Frequency Distribution of Data
- Diagrammatic Presentation of Data
- Graphic Presentation of Data
- Measures of Central Tendency
- Mean Median Mode
- Measures of Dispersion
- Standard Deviation
- Variance Analysis
Essentials of a Sample Investigation
Some critical essentials of sampling include:
- Representativeness – You must select the sample in a manner which represents the universe in its truest sense. Further, if you fail to do so, then you might get misleading results.
- Adequacy – You should also select the size of the sample adequately which represents the parametric characteristics of the population.
- Independence – When you select a sample, you must ensure that you select the items independently and also randomly.
- Homogeneity – This is another important element of a sample investigation. Homogeneity means that there is no basic difference in the nature of the units in the sample and the universe.
Merits of a Sample Investigation
Here are some important merits of sampling:
- Cost-efficient – In a sample investigation, the costs associated with the collection of data are less. This is because you collect data only from a fraction of the entire population. Therefore, it is cost-efficient.
- Time-efficient – In sampling, you require less time to collect, analyze, and interpret the data since you are working only on a fraction of the population. Hence, it is time-efficient too.
- Reliable – Usually, the data collected under a sample investigation is reliable because of the use of well-trained and experienced investigators or experts.
- Flexible – When you collect data through sampling, you have a greater scope of flexibility.
- Detailed Information – Since sampling is cost-efficient and also time-efficient, you can collect detailed information about the sample in your survey.
Demerits of a Sample Investigation
While sampling has many merits, there are some demerits associated with it too. Here is a quick look:
- It is impossible to attain a 100 percent accuracy using this process. This is because the investigator draws conclusions about the characteristics of the population using the results that he obtains from the selected sample.
- The results are prone to a sampling error or a random error.
- Experts are required to ensure that the results of a sample investigation are satisfactory.
- Sometimes, the sample does not represent the population correctly. This is because it depends on the attitude and mindset of the investigators.
- If the population has a heterogeneous character, then you cannot use this method.
Solved Question
Q1. What are the essentials of a Sample Investigation?
Answer: The essentials of sampling are:
- The sample must truly represent the population
- Its size must be adequate
- You must select the sample randomly and independently
- The population must be homogeneous