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How Can We Ensure Our Data And Codes Are Accurate In Our Research?

How Can We Ensure Our Data And Codes Are Accurate In Our Research?


This is a good question. According to Skjott Linneberg & Korsgaard (2019), the coding of data in research transforms the collected data into cohesive and meaningful cohesiveness and represents the data to offer a systematic account of the observed or collected data. Therefore, the accuracy of the data influences the quality of the research. One of the things that can be done to ensure that data is accurate is aligning the key parameters and factors that contribute to the accumulation of the data and determining the most relevant factors that are needed for analysis. The second thing is using a computerized system to record data to avoid human errors. Data accuracy can also be enhanced by triangulating data sources. Besides, Bans-Akutey & Tiimub (2021) argue that the triangulation of data sources includes applying three methods or approaches to verify data. For example, a researcher can use key informant interviews, household interviews, and focus groups to reduce errors. Triangulation requires using the information provided by individuals with predetermined attributes, knowledgeable people, and a multi-sectorial group.

Coding in research requires identifying the type of codes a researcher intends to use. According to Nair (2013), codes are classified into final and preliminary. Final codes are used to observe a pattern in data. Consequently, initial codes ensure that the data gathered is concise. Researchers can ensure that codes are accurate by using coding software such as thematic or text analytics software. In manual coding, the accuracy of data codes can be guaranteed by selecting the data coding approach, reading through the data to understand its structure, categorizing the data codes, determining how they fit into the coding frame, and identifying the themes that occur frequently. A researcher can use inductive or deductive coding. Inductive coding includes creating codes based on the collected qualitative data. Deductive coding, however, includes starting with a predefined set of data codes and then assigning the codes to new qualitative data.


Bans-Akutey, A., & Tiimub, B. (2021). Triangulation in Research. Academia Letters.

Nair, G. (2013). Ensuring quality in the coding process: A key differentiator for accurately interpreting safety data. Perspectives in Clinical Research4(3), 181.

Skjott Linneberg, M., & Korsgaard, S. (2019). Coding qualitative data: a synthesis guiding the novice. Qualitative Research Journal19(3), 259-270.


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How Can We Ensure Our Data And Codes Are Accurate In Our Research.

How Can We Ensure Our Data And Codes Are Accurate In Our Research?

About my last discussion that you did, can you answer this question?

Shajaira, thanks for sharing these two research studies with the class. You made some excellent points. Errors in data collection or coding can play a significant role in the outcomes of a survey. This is important to know, as coding can be very complicated. If data collection errors occur, the results will not be accurate. How can we ensure that our research data and codes are correct?

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