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An analysis on video game sales using R language and k-means clustering algorithm

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Analysis-on-Video-Game-Sales

Early on, development costs were minimal, and video games could be quite profitable. Games developed by a single programmer, or by a small team of programmers and artists, could sell hundreds of thousands of copies each. As computing and graphics power increased, so too did the size of development teams, as larger staffs were needed to address the ever-increasing technical and design complexities. The larger teams consist of programmers, artists, game designers, and producers. Their salaries can range anywhere from $50,000 to $120,000 generating large labor costs for firms producing videogames which can often take between one and three years to develop. Now budgets typically reach millions of dollars. In addition to growing development costs, marketing budgets have grown dramatically, sometimes consisting of two to three times of the cost of development. Today the global video game market is valued at over $93 billion.
With the advancement of electronic products and communication technology in modern society. As a derivative product, video games are increasingly entering people's vision. This dataset contains a list of video games with sales greater than 100,000 copies. It was generated by a scrape of vgchartz.com.

In this project, we have performed the following using R:

  • Exploratory Data Analysis
  • Data Visualization
  • Hypothesis testing to check if the mean between sales of North America and Japan are equal
  • Performed k-means clustering algorithm on the top 100 video games sold to compare and classify the data

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