- Purpose
- Background
- Overview of Analysis
- Challenges or Difficulties
- Conclusions on 'Theater Outcomes by Launch Date'
- Conclusions on 'Outcomes based on Goals'
- Limitations and Potential Tables/Graphs
Purpose & Background
Louise's play, Fever, came close to its fundraising goal. She wants to compare her results by analyzing the outcome for different campaigns in relation to their launch date and funding goals.
By utilizing the Kickstarter dataset we will visualize how the launch date and funding goals affected the campaign outcomes.
Overview of Analysis
In this graph we observe what percentage of theater outcomes were successful, failed, or canceled in relation to their launch date. There seems to be an almost neglible amount of theater campaigns that were canceled. The amount of ones that have failed seem almost uniform throughout the year with an estimate of 40. The amount of theater campaigns that were successful seemed to be at its most during the month of May with an estimate of 110, which far exceeds the beginning and end of the year.
In this graph we observe what percentage of plays were successful, failed, or canceled in relation to their fund raising goals. There is no line on the graph indicating percentage canceled because there were no plays that were canceled for any range of the fundraising goals. We can observe that the highest percentage of plays successful were the ones with the lowest fundraising goals. The goal range of 'less than 1000' is the highest peak of almost 80% of plays being successful. However, there seems to be a spike upwards in percentages successful around the goal range of $35,000 to $45,000 resting around 70%.
Challenges or Difficulties
Theater Outcomes by Launch Date:
This graph could be skewed in its results due to it not representing well the grand total of theater campaigns occuring every month. Even though we see a peak of successful campaigns in May and June, during these months there were more theater campaigns being held than any other month so there was more oppurtunity there to see more successful campaigns. There were at least 40 more theater campaigns held in May than most of the other months. Going as so far to even having more than double the amount than those held the month of December.
Outcomes Based on Goals:
This graph contains an unnecessary factor in showing the percentage of failed plays. The line showing the percentage of successful plays should suffice seeing how any play that was not successful is the percentage of failed plays. However, this is only because there was a 0% of canceled plays. If any amount of plays were canceled then showing all the lines would be good indicators. This graph could also be misleading because it only shows a percentage, not the flat amount of plays that were held under these goal ranges. The total amount of plays held that were within the goal range of less than $10,000 is about 850 while the range of $10,000 and above is about 120. The graph shows that a high percentage of plays were successful around the $35,000 to $45,000 range but there were only 9 plays being held in that range.
Conclusions on 'Theater Outcomes by Launch Date'
From the data and graph given we observe that theater campaigns that launched in May had the highest amount of success while the ones that had a launch date at the beginning and end of the year had the least. The theater campaigns with launch dates in the beginning and end of the year had almost just as many that have failed as well. There was a little to negliable amount of theater campaigns that were canceled throughout the year.
Conclusions on 'Outcomes based on Goals'
From the data and graph given we observe plays found more sucess when the fundraising goal was lower.
Limitations and Potential Tables/Graphs
Starting with 'Theater Outcomes by Launch Date' we can see there are a few limitations. There seems to be a staggering amount of theater campaigns that were successful during the month of May, but during that month there was when the most amount of theater campaigns were held. So it is difficult to say which month held the best results with these metrics and graph. An additional data set we could add would be percentage of successful, failed, and canceled for each month. As for the graph, a line graph could still work with the percentages or we could even do a pie chart.
The 'Outcomes based on Goals' runs into the opposite issue where the percentage is misleading. Majority of the goal ranges had less than 10 plays in each range while there are over 850 plays that were in the ranges of 'less than 1000', '1000 to 4999', and '5000 to 9999'. We observe the flat amount in the dataset showing the number of plays that were successful, failed, or canceled. This could be displayed on the graph as opposed to the percentages. For information such as this a bar graph could show the data in a cleaner manner.