Great question!
How do you make a good visualization? You might ASK yourself that and I actually use that as an acronym to help me remember. Really, what it comes down to, is accurate story knowledge. If you can create visualizations that are accurate, and that tell a good story, even if it's not a linear story. And provide real knowledge to your audience then that's a good target to shoot for. What do you think? What makes a good data visualization? Let's have a positive and warm discussion!! :)
In my opinion, a good method of visualizing quantitative data is firstly their processing, conducting statistical analysis and in the formula Business Intelligence and then based on properly processed research results drawing charts, etc.
Best wishes
Use similar photos representative of data and proportional size of photo to make it understand
The data (in excel file) can be visualised by using pivot table/ chart using MS- Excel. The other approach is making bar charts and pie-charts (if total frequencies add upto 100%).
I like your ASK acronym, Mohammed Kemal
Accurate
Story
Knowledge
I'm going to share that one with my students.
Thank you!
Back to you discussion, I think it's important to make a visualisation clearly understood. A visualisation that communicates is not necessarily one that looks the most pretty, or the most spectacular. One piece of advice I read once (Stephen Few?) is that a chart needs to be understood within 3-4 seconds, without having to read any notes or explanation on how to interpret the figure. Data-Ink ratio helps a lot with that test. (more recently called Data-Pixel ratio)
When designing a data visualization, we must first clearly consider our target audience.
Through:
* what medium will the data visualization be conveyed and for what purpose?
* What’s the skill level of your audience?
*What response do you want to invoke through the visualization?
there are many open source software like 'R' and python available that are used for data visualization. The most important part of it is what you want to convey to audience.
In a data set, there are many variables (may be some are independent and some are dependent), that we have to select. Again the data are metric data or non-metric we have to find out. For the process analysis, please follow Hair et.al. 7th ed., page no 15, table 2. Most important is what you want to convey your audience from your research by showing such data.
I believe that during visualization it is necessary to manage with three main requirements: 1. visibility; 2. unity of conventions; hence, in my opinion, the main requirement is reversibility. Ultimately, we visualize in order to draw a conclusion and make a decision.