Question: Instructions: Read https://www.uschamber.com/co/good-company/launch-pad/pandemic-consumer-habits. The article cites several statistics and analytics as a result of a study on consumer habits since the Covid pandemic. Select ONE

Instructions:

  • Read "https://www.uschamber.com/co/good-company/launch-pad/pandemic-consumer-habits".
  • The article cites several statistics and analytics as a result of a study on consumer habits since the Covid pandemic. Select ONE of the statistics cited. Assume you want to test this statistic with your own study. Discuss the following:
    • Which statistic cited in the article do you plan to test or challenge?
    • How would you set up the null and alternative hypotheses to begin this study? You can choose to test for a "change", an "increase", or a "decrease". For clarification consider the following example:
      • For example, at the end of the article, it cites a study performed on 1900 consumers who purchased a home during the pandemic. The study concludes that "63% of the recent homebuyers admitted they purchased just from viewing online...". To test this finding, assume I want to determine if homebuyers in Kansas were higher than this national proportion. Therefore, my hypotheses would be:
        • Ho: Proportion 63%
        • H1: Proportion > 63%
        • And no, you cannot use this example! :)
    • Refer to "Statistical Inference" topic from the book and the distinctions between a Type I Error and a Type II Error. In particular, focus on the difference between a "false alarm" and a "missed opportunity". With specific regards to your proposed hypothesis test procedure, what would a Type I Error (false alarm) mean? What would a Type II Error (missed opportunity) mean?
      • For example, given my hypotheses in my example above, a Type I Error would be concluding that the proportion of Kansas homebuyers during the pandemic who purchased their home just from viewing online is greater than 63%, when it is actually less than or equal to 63%. A Type II Error would be concluding that the proportion of Kansas homebuyers during the pandemic who purchased their home just from viewing online is less than or equal to 63%, when it is actually greater than 63%. (And no, you cannot use this example either! )

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