Which of The Following Statements is True Concerning Data Selection

Question: Which of the following statements is true concerning data selection?

1. A data selection strategy is required by federal law
2. Establishing a data selection strategy prior to collecting data decreases the chance of a biased outcome
3. A data selection strategy must be established after the data are collected
4. A good data selection strategy can eliminate the need for data collection

Answer: Option (b) Establishing a data selection strategy prior to collecting data decreases the chance of a biased outcome.

One needs to decide on a data selection strategy for a perfect research plan. However, the data selection process depends on various segments. But before digging deep into the process, let's have a quick look at the meaning of the data selection process.

Data selection takes into account the various data types and is a process of defining all of them. The process plays a major role in various business processes. Data selection depends highly on the sources and considers selecting a specific set of data from a big database for further analysis. The process aims to find data specific to the objective and reduce the impact of unimportant and repetitive data.

Organizations need to work on massive data to formulate business strategies for a better future. Hence, it is crucial to find the best strategy to identify relevant data and use them to plan things well. Federal law emphasizes on submitting data strategy for companies working on a massive database.

You must select the correct method to simplify the data selection process. For those who are not well-acquainted with the process, here's a list of the best data selection methods you must take into account:

• Simple random sampling
• Cluster sampling
• Systematic sampling
• Stratified sampling

The method depends on a lot of factors. The first and most important factor is the research question or objective. You have to understand the objective of the research, understand the type of data necessary to answer the question, and select a method accordingly. You must also consider the data quality and choose a method that can help you find high-quality data. It is necessary to use data that is appropriate and completely free from errors, biases, and inconsistencies.

In addition, it is also important to consider the size and diversity of the dataset while collecting data. You must ensure that the dataset is strong enough to help you prove your point to justify the solution.

Make a note of the points if you are asked to work on a massive dataset. Understand the essence of selecting a data selection strategy to find relevant data for your research.

Frequently Asked Questions

1. What are the methods of data collection?

There are four types of data collection methods, namely:

• Observational
• Experimental
• Simulation
• Derived

Understand the meaning of each of the methods to work on the data collection process and find appropriate data.

2. What are the considerations in data selection?

You need to consider a lot of things in the data selection process. It is crucial to determine the correct type and data source that can help you answer the questions correctly. Also, you must find the correct procedures and instruments to find the necessary data.

3. What does the choice of data selection depend on?

You have to consider three things to make the choice of data selection, namely:

• Aim and objective of the study
• Type and distribution of data used
• Nature of observations (paired/unpaired)

All these factors are necessary for selecting data appropriate to the research question.

4. Which data collection method takes less time to complete?

Out of all data collection methods, the secondary method involving both qualitative and quantitative techniques takes less time to complete. The information is easily available, and you will not have to invest a lot of time in searching for appropriate information.

5. What are the common challenges in data collection?

The common challenges in data collection are:

• Data quality issues
• Finding relevant data
• Deciding on the data to gather
• Dealing with big data
• Low response and several other issues with the research

You must know to deal with these challenges to find relevant data for your research.