Let’s start with the important question – what exactly did you get? If it’s an empirical research paper, what you’ve got is a number, or more precisely, a statistic, and you need to explain this data. Here’s an example of how to interpret statistical data significance based on Pearson’s correlation coefficient:
The values range between -1 and 1, where 1 indicates a strong positive relationship, and -1 indicates a strong negative relationship. The closer the numerical value is to either end of the spectrum, the stronger the correlation. Here’s a table explaining the received values:
| From Value | To Value | Interpretation of Received Value |
| -1 | -0.9 | Very strong negative correlation |
| -0.9 | -0.7 | Strong negative correlation |
| -0.7 | -0.4 | Moderate negative correlation |
| -0.4 | -0.2 | Weak negative correlation |
| -0.2 | 0 | Very weak or negligible negative correlation |
| 0 | 0.2 | Very weak or negligible positive correlation |
| 0.2 | 0.4 | Weak positive correlation |
| 0.4 | 0.7 | Moderate positive correlation |
| 0.7 | 0.9 | Strong positive correlation |
| 0.9 | 1 | Very strong positive correlation |
Additional data such as statistical significance level, standard deviation, degrees of freedom, etc., also need to be considered. However, it’s worth noting that when we’re dealing with writing a research paper, the writing process, data collection, selection of articles, understanding the findings, writing discussions and conclusions, and creating a high-quality integration between the chapters are what will ultimately determine your grade. Although we don’t diminish the importance of quality statistical inference, (on the contrary, we are quite fans of it), we recommend focusing on the way you write and conduct your research.
After understanding the statistical significance of your findings, it’s time to write them down in the findings chapter. It’s recommended to add tables that outline the correlation coefficient and briefly summarize the received findings. Here’s an example of how to write findings:
Table 9: Correlation between Purchasing Food Products and Positive Recommendations
| Purchasing Food Products | Positive Recommendations | |
| Purchasing Food Products | 1 | **0.794 |
| Positive Recommendations | 1 |
**p<.01
From the findings (Table 9), it is evident that there is a significant positive relationship between the purchase of food products and numerous positive recommendations from consumers (p<.01, rp = 0.794). In other words, the more positive the recommendations, the more likely people will buy the food. The hypothesis is confirmed.
But what happens when we’re dealing with theoretical findings? Or the question of all questions – how do you extract findings from endless interview transcripts? And here we go back to the beginning – building coherent and well-structured interview questions based on your hypotheses, which will give you more organization and clarity when you come to extract your findings. Our recommendation is to prepare several aspects that came up in the interviews. For example, if you asked, “What are the challenges faced by members of the Ethiopian community in integrating into society?” We can extract from the question itself the themes we hypothesize will emerge:
Discrimination
Community and cohesion
Education
Socioeconomic status
Family support, and more.
Now, it will be easier for us to extract the relevant quotes from the interviews at our disposal. We’ll categorize the quotes according to the themes and create a wonderful findings chapter that contains quotes, conclusions, and everything divided, organized, and most importantly – pleasant and easy to read.
And what about the findings chapter in a theoretical work? Well, the heart of the theoretical work is the findings. For example, if we wanted to list off the reasons for the dissolution of the Soviet Union, we can divide the chapters according to the reasons that lead to the findings of the work. All that remains is to move straight to the discussion and conclusion chapters.
