Over $2 billion has been raised using the massively successful crowdfunding service, Kickstarter, but not every project has found success. Of the more than 300,000 projects launched on Kickstarter, only a third have made it through the funding process with a positive outcome.
Getting funded on Kickstarter requires meeting or exceeding the project’s initial goal, so many organizations spend months looking through past projects in an attempt to discover some trick for finding success. For this week’s homework, you will organize and analyze a database of 4,000 past projects in order to uncover any hidden trends.
Create a new space for this project called excel-challenge
in either DropBox or Google Drive. Do not add this homework to an existing space.
Store your excel workbooks in here and create a sharable link for submission.
Using the Excel table provided, modify and analyze the data of 4,000 past Kickstarter projects as you attempt to uncover some market trends.
Use conditional formatting to fill each cell in the state
column with a different color, depending on whether the associated campaign was successful, failed, or canceled, or is currently live.
Percent Funded
that uses a formula to uncover how much money a campaign made to reach its initial goal.Use conditional formatting to fill each cell in the Percent Funded
column using a three-color scale. The scale should start at 0 and be a dark shade of red, transitioning to green at 100, and blue at 200.
Create a new column P called Average Donation
that uses a formula to uncover how much each backer for the project paid on average.
Create two new columns, one called Category
at Q and another called Sub-Category
at R, which use formulas to split the Category and Sub-Category
column into two parts.
Create a new sheet with a pivot table that will analyze your initial worksheet to count how many campaigns were successful, failed, canceled, or are currently live per category.
Create a stacked column pivot chart that can be filtered by country based on the table you have created.
Create a new sheet with a pivot table that will analyze your initial sheet to count how many campaigns were successful, failed, or canceled, or are currently live per sub-category.
Create a stacked column pivot chart that can be filtered by country and parent-category based on the table you have created.
The dates stored within the deadline
and launched_at
columns use Unix timestamps. Fortunately for us, there is a formula that can be used to convert these timestamps to a normal date.
Create a new column named Date Created Conversion
that will use this formula to convert the data contained within launched_at
into Excel’s date format.
Create a new column named Date Ended Conversion
that will use this formula to convert the data contained within deadline
into Excel’s date format.
Create a new sheet with a pivot table with a column of state
, rows of Date Created Conversion
, values based on the count of state
, and filters based on parent category
and Years
.
Now create a pivot chart line graph that visualizes this new table.
Create a report in Microsoft Word and answer the following questions.
Create a new sheet with 8 columns:
Goal
Number Successful
Number Failed
Number Canceled
Total Projects
Percentage Successful
Percentage Failed
Percentage Canceled
In the Goal
column, create 12 rows with the following headers:
Using the COUNTIFS()
formula, count how many successful, failed, and canceled projects were created with goals within the ranges listed above. Populate the Number Successful
, Number Failed
, and Number Canceled
columns with this data.
Add up each of the values in the Number Successful
, Number Failed
, and Number Canceled
columns to populate the Total Projects
column. Then, using a mathematical formula, find the percentage of projects that were successful, failed, or canceled per goal range.
Create a line chart that graphs the relationship between a goal’s amount and its chances at success, failure, or cancellation.
If one were to describe a successful crowdfunding campaign, most people would use the number of campaign backers as a metric of success. One of the most efficient ways that data scientists characterize a quantitative metric, such as the number of campaign backers, is by creating a summary statistics table.
For those looking for an additional challenge, you will evaluate the number of backers of successful and unsuccessful campaigns by creating your own summary statistics table.
Create a new worksheet in your workbook, and create a column each for the number of backers of successful campaigns and unsuccessful campaigns.
Use Excel to evaluate the following for successful campaigns, and then for unsuccessful campaigns:
The mean number of backers.
The median number of backers.
The minimum number of backers.
The maximum number of backers.
The variance of the number of backers.
The standard deviation of the number of backers.
Use your data to determine whether the mean or the median summarizes the data more meaningfully.
Use your data to determine if there is more variability with successful or unsuccessful campaigns. Does this make sense? Why or why not?
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