Data Analyst on Excel projects to determine if they are successful nor fail. Measuring the success on Kickstart. Create tables, graphs, color shades, etc.
Using the Excel table provided, modify and analyze the data of 4,000 past Kickstarter projects as you attempt to uncover some market trends.
The given data shows theater is the most popular category with a high success rate of 60.2 percent. The highest funded percentage would be technology. It makes up 69.7 percent of the total funding. Finally, in the sub-category is the play's with a success rate of 65.1 percent, and a fail rate of 33.1 percent.
How, why, and what have the kick-starters fail. The data did not have enough indicators to determine if the kick-starter would fail or succeed because it could have been the lack of advertisement, workers, stories, etc. If given information on the 'causes of the kick-starters to fail would improve the data and a sense of understanding of the negative and positive indicators. A positive indicator would be the amount of funding into advertisements. The data on an advertisement would be one of the variables that would help decide what makes a kick-starter successful. Another indicator would be the staff or team. Behind every kick-starter needs a solid team to be successful. These are examples to help improve the data and reduce weaknesses in the analysis.
Some other possible tables and graphs we could make are the percentage of success and failure rate. In categories and sub-categories, its data can show which kick-starter will have a greater chance to be successful. For example, there are about 2,185 out of 4,114 that are successful in reaching their funds. This number tells us that it has a success rate of 53.1 percent. The failure rate is 37.2% meaning 1,530 has failed. Also, the category theater has a success rate of 60.2 percent (839/1393) and a fail rate of 35.4 percent. Another table would be graphs and tables of the percent funded for each category and sub-category. In the graphs, we can see each category and sub-category has received the most funds.
The average of backer counts is 113 with a median of 25. It tells us that there will be parts of the data that are off. The kick-starters with more back counts would have the advantage to receive extra funds and support to reach their goal. Due to the gap between average and median, it will impact the outcome of the data.
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