To save this table, just click on the “Export” button, and ATLAS.ti will open up the table directly in Excel. Thus, you can choose whether you want to see the relative frequencies of the data in the columns, rows, and/or whole table (you can select one, two, or all three options to view them in the table at the same time). On the other hand, 40% of the data regarding power that comes from Liao (2017) is about referent power. Looking at the table, we can see that 50% of the data regarding power that comes from Avolio and Kahai (2003) is about informational power. In ATLAS.ti 8 Windows, click on “Normalize” in the ribbon toolbar in ATLAS.ti 8 Mac, click on “Options” and select “Normalize.” What do we do now?įortunately, ATLAS.ti is here to help! You can normalize these frequency counts: the numbers are automatically adjusted by taking the size of the document into consideration. Therefore, we cannot make accurate comparisons based on just these absolute frequencies. However, what if Liao (2017) is a 30-page article, while Avolio and Kahai (2003) is a 10-page article? Well then, these results are slightly distorted as there is more data (i.e., there are more quotations) in Liao (2017) in comparison to Avolio and Kahai (2003). Right now, the table is showing us the absolute frequencies of these codes. Below the table, we can see a preview of these four quotations (and by clicking on any of the quotations, you can see it back in its original document ATLAS.ti always keeps you close to your data!). We can already see that, in comparison to Avolio and Kahai (2003), Liao (2017) talks more about online leaders using referent power. In other words, it seems that Liao (2017) mentions online leaders using referent power four times. You can see that the code “Power: Referent” was used four times in document 4 “Liao (2017)”. In the above example, we are examining how many times the different types of power were mentioned across two articles from our literature review. View normalized frequency counts and relative frequencies
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