REFLECTION #5
I consider that cleaning data is like cleaning my room up before my friends come over – some of my classmates said they consider it important and others feel it is confusing and makes things messier. Cleaning data is key to getting ready for analysis and making sure it’s actually useful. But there’s a whole debate about whether it’s ethical because while it can make data more accurate, it might also leave out important stuff or make things seem better or worse than they really are. This pretty much happened with our survey for our research class. Some of our questions got misunderstood and the answers were either vague or people just didn’t respond to them.
There is people who think it’s important to deal with any fuzziness or uncertainty in the data using graphs and stats, and they’re big on keeping everything transparent so everyone can see how the data was handled. They also think it’s smart to hang onto the original data, just in case anyone wants to double-check.
But some people say you can overdo it with the cleaning. They worry that cleaning the data too hard might wipe away important details and make things more confusing. Plus, cleaning could actually make biases worse or leave out voices that need to be heard, which isn’t great for doing honest research.
In the end, it’s all about finding the right balance. Cleaning data can make it better for analysis, but it’s important to think about the ethics behind it. That means being careful about what gets cleaned and how it’s done, so we can keep the data accurate and fair for everyone.
I loved my first experience cleaning data cause it helped me and my team to do a better job on our interview questions and in the future it will help us with our final project. In what ways you might ask. Well, with this we can be more objective, and professional and we will avoid being vague with our conclusions.
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