8 Mistakes to Avoid When Using Secondary Data Collection in Your Research
Research can take months or sometimes years, depending on the subject matter. Accurate data collection is the key to conducting successful research. Nowadays, secondary...
Research can take months or sometimes years, depending on the subject matter. Accurate data collection is the key to conducting successful research. Nowadays, secondary data collection replaces primary data collection because it requires less time and effort to collect and analyse information. Moreover, with this data collection method, researchers improve the delivery of results.
Gathering information through secondary data collection techniques is like finding a treasure. However, when you collect data from secondary sources, various mistakes can hinder its accuracy. Proper planning and execution are necessary to accumulate accurate and reliable data while using this method.
If you are conducting research for your dissertation and are afraid of falling into the trap of mistakes, then this blog is for you. Here, we shall give you a list of all possible mistakes that you should avoid while collecting secondary data. In addition to this, we shall also discuss some secondary data types and collecting methods for your better understanding.
So, let’s start reading this article:
Secondary Data Collection Methods
Secondary data collection refers to extracting data from already existing sources. In other words, in this data collection method, the researcher does not collect new data, but he uses data that was previously gathered by someone else.
However, sometimes, it becomes an uphill task for students to collect relevant information from already existing sources. Here, most students request professionals to help them with their dissertations so that they can compose a well-researched document. Whereas others prefer to gather secondary data from various sources, such as:
Accessing Data from Online Journals and Publications
Educational institutes publish their research work or journals online, which are easily accessible to everyone. This is the prime source of secondary data. Moreover, these are the most reliable data sources for research purposes.
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Collect Information through the Internet
Collecting information through the Internet is the most popular secondary data collection methodology. It goes without saying that on the internet, you can access reliable information with just a few clicks. Additionally, you can get information on the internet free of cost, although some websites charge a minimal amount to provide data.
Consult Government and Non-Government Records
Generally, government institutes or organisations save data for research purposes. This data encompasses statistical records, research results, and population figures. You can consult these organisations to gather secondary data for your research.
Assess Business Records
Business organisations usually release reports of financial revenue and market trends. These records serve as secondary sources and are used for industry-based research. This information is readily available to the public, so you can access these records at any time from anywhere.
Looking Publish Data by Libraries
Libraries have a vast collection of publications, books, journals, and magazines that are available free of cost for everyone. These sources of information are the most authentic and reliable.
As we have discussed the most common methods for collecting secondary data, here are some mistakes that most of the students make during the secondary data collection process. Let’s read them in detail:
Common Mistakes to Avoid When Using Secondary Data Collection in Research
Data collection is hard, and secondary information collection is harder for a beginner. Many academic scholars make mistakes that lead their research in the wrong direction. The following are the most common mistakes that research students must avoid to make their research projects successful.
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Your research question guides you from collecting data to writing your research report. Starting your research with poorly designed questions is one of the most common mistakes of researchers. Moreover, a complex, double-meaning, and vague question to collect information can affect the accuracy and reliability of your secondary data.
You can avoid this mistake by following the below-mentioned tips:
- Use simple and clear words.
- Avoid technical terms.
- Pre-test your question.
Measurement Error
Measurement error occurs when your secondary data is not in accordance with your research question. This error usually happens due to the following reasons:
- Use of the faulty instrument.
- Having unclear instructions.
- Inappropriate scaling factors.
You can use reliable instruments to prevent this error. You can also pilot-test these equipment to ensure their reliability and validity. In addition to this, you must ensure that your instruments are appropriate for your research question, data analysis method, and your subject matter.
Sampling Bias
Sampling bias happens when your research is not a representative sample of your target audience. In simple words, you collect secondary data from a group of people in which some members have higher or lower sample probability as compared to others.
This imbalance of probability can affect the validity of your research and can make it difficult for you to conclude your research on the generic spectrum. You can avoid this mistake by following below-mentioned practices:
- Use the best sampling method.
- Ensure that your probability size is large and diverse enough.
- Continuously monitor your response rate.
Relying on Unreliable Sources
In the era of rapid data processing, data manipulation happens more than ever before. It goes without saying that in secondary data, there are higher chances of inaccuracy and unreliability. There can be many reasons for this unreliability, including:
- Duplicate information
- Missing data
- Rounding errors
- Outdated data
In order to remove this kind of mistake, you must ensure the validation and quality of the secondary data that you gather for online sources. Furthermore, this data validation helps you to determine internal and external inconsistencies in your data that eventually make your research powerful and authentic.
Fail to Analyse Data
In secondary data collection, the researcher usually isn’t involved in extracting information from original research work. Therefore, while analysing secondary data, he may fail to interpret data accurately.
Needless to say, secondary data must be collected to answer your research question, so you have to interpret it and extract useful information that supports your arguments. Therefore, try to evaluate this data on certain criteria to ensure its validity. These criteria are the following:
- Methodology of data collection.
- Accuracy of the data.
- The purpose of collecting this data.
Inappropriate Data Cleaning
Neglecting adequate data cleaning is one of the most common mistakes that a researcher usually makes. Data cleaning is a process of highlighting and correcting mistakes, inconsistencies, and inaccuracies during the analysis of secondary information. This data cleaning can help the researcher in many ways, including:
- Identifying duplicate data
- Pointing out invalid entries
- Detecting extreme values
In a nutshell, collecting secondary data is not a piece of cake; you need to follow various precautions to avoid the most common mistakes. Besides this, hiring dissertation writing services from The Academic Papers UK is another best solution to get rid of all the mistakes that you can make during data collection.
Unethical Data Practices
Sometimes, research students extract information from a secondary source but don’t cite this reference. This mistake is known as unethical data practices and affects the student’s credibility. Below, we have shared various forms of unethical data, including:
- Add data without consent.
- Misuse secondary data.
- Present other’s work as yours.
To make your research project successful, you need to adhere to the data collection rules and regulations. Also, you can follow some tips that help you avoid unethical data practices. These are:
- Respect others' work by citing.
- Maintain the integrity of their work.
- Protect data from falsification.
Lack of Critical Analysis
Extracting data from secondary sources without critical analysis is one of the greatest pitfalls in a research project. Data collection from primary and secondary sources is not about just summarising information. However, you need to add your interpretation and viewpoint on the collected data.
For instance, if you are taking data from a survey, critically analyse it and identify any potential limitations and factors that can influence this survey. Moreover, with the in-depth analysis, you may:
- Analyse your data effectively.
- Understand the purpose of your research.
- Present alternative views.
As you go through some common errors students make while data collection, now take a look at how someone can conduct secondary research without making the above-mentioned mistakes.
How to Conduct Secondary Research?
Secondary data may be inappropriate and invalid for your research, so you need to be meticulous when conducting secondary research. Here, we are going to enlist all the essential steps that you must follow to make your research successful. Let’s start.
Determine the Research Question
Before jumping into the research, first, identify the purpose of your research project. When you determine your research question, you can carry out valuable investigation and analysis.
Identify Reliable Resources
Collecting research data from secondary sources is tricky. You need to be careful to avoid unreliable or false data accumulation. Therefore, after determining the research topic, narrow down the resources and figure out the relevant ones.
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Collect Relevant Data
Once you shortlist all the reliable resources, it is time to extract relevant data from these sources. You can collect relevant data from various sources, including books, publications, and magazines.
Compare and Analyse Data
After gathering relevant data, compare and analyse this information to identify any duplications and inaccurate data. Interpret your data and ensure all the necessary points are included in this data.
Advantages of Secondary Data Collection
One key characteristic of the secondary data collection is that the researcher did not take part in the actual data collection method. This data is collected by someone else who gathered it for his own research purpose. This key characteristic brings many advantages to this data collection method.
Cost-effective
Most secondary sources are free of cost or available at very low prices. Unlike primary data collection, this method doesn’t require conducting research from the beginning. In a nutshell, when you compare primary data collection to secondary data, secondary data overshadows primary data.
Less Time-consuming
One of the greatest advantages of secondary sources is that data collectors don’t need to waste time on extensive research. All in all, researchers just go through a few Google searches to gather valuable information.
Ease of Access
Secondary data sources are easily available for everyone in this digital era. The Internet made this data easily accessible to all. With just a few clicks, you can gather vast information for your research.
Longitudinal Analysis
Longitudinal analysis means research is being performed over a huge spectrum of time. Secondary data collection helps students to conduct this analysis. Furthermore, you can find data on specific research from many years ago to a few hours before.
Give New Insights from Previous Data
Secondary data accumulation opens doors for new ideas and opportunities for research students. Moreover, by analysing and understanding the previous work, they craft their own viewpoints or events to make a conclusion relevant to the previous studies.
What are the Four 4 Types of Secondary Data?
Secondary data allows researchers to gather information about the background and future perspectives of a specific study. Four major types of secondary data are the following:
Internal Secondary Source
Internal secondary data is collected by an organisation or individual internally and stored for future use. After conducting in-depth research, they stored reliable data in the information warehouse and sent inaccurate data to the data lakes. Sales reports, customer databases, and previous research are included in this secondary data type.
External Secondary Source
Organisations collect information from external sources, which is called external secondary data. This data is considered useful when conducting research for a new scope. Additionally, these sources include government sources, publications, and libraries.
Qualitative Secondary Source
Qualitative data is all about the qualities of a specific event that are expressed in words, observations, and symbols. This information cannot be written in numbers or figures. Moreover, the need for this secondary source arises due to research strands.
Quantitative Secondary Source
The quantitative source is the statistical manipulation of secondary data, which is expressed in numbers and is the most reliable secondary data source for research.
Conclusion
Secondary data collection involves referring to information that was collected from primary resources by someone else. Nowadays, this data collection method is popular as compared to primary data collection because it is less time-consuming, cost-effective, and easily accessible. However, researchers make mistakes while gathering information through this method.
Are you afraid to become one of them? No worries. Buy a dissertation online from UK-native PhD-qualified writers who know how to collect reliable secondary data and make your writing process seamless.
If you want to collect data and write your dissertation by yourself, then avoid the mistakes we have highlighted in this guide. By removing measuring errors, reducing sample biasing, interpreting data correctly, and preventing unethical data practices, you can write a winning research paper.
