To perform this analysis, we had to add columns to the original data sheet. We added “Parent Category”, “Subcategory”, “Date Created Conversion”, “Date Ended Conversion”, and “Years”. See the spreadsheet here. We then created a pivot table to display the theater outcomes vs launch. We used parent category and years as the filters, outcomes as the columns, date created conversion and the rows, and count of outcomes as the values. Then we added the title of “Theater Outcomes vs Launch” and saved this chart as a png.

To perform the “Outcomes Based on Goal” analysis we created a new sheet to organize the data pulled from the main spreadsheet to get the number of successful, failed, and canceled campaigns. See the spreadsheet here. Then we categorized them based on goal amounts and calculated the percentage of each based on the total number of projects with the goal range. We created the “Outcomes Based on Goal” chart to represent this data and saved it as a png.

I did not encounter any challenges with processing and representing the data. There could be possible challenges with pulling the data from the Kickstarter sheet to the Outcomes.

This concludes that May is the best month to start a theater campaign and December is not.

This concludes that goals that were less than $4,999 and between $35,000 and $44,999 were 73% and 67% successful, so setting a goal under $5,000 with a strong play name has the highest likelihood of success.

Some limitations of this dataset are that it does not give information on the organization who performed the plays and there is no data on how much each performance made. While this dataset is helpful for selecting which plays get this most and lest amount of funding it doesn’t include how the overall success of programs.

One possible table and/or graph we could create would be a chart showing the goal donation amount vs the pledged amount and the statistical data showing distribution from of the standard deviation. Another possible table and/or graph could be the name of certain plays vs the success rate of the play and amount pledged compared to the goal.