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  3. Causal Inference with R - Regression

Exercise

Practice with Survey Weights: Part 1

Given the diversity of people in the United States, many surveys have difficulty gathering perfectly representative samples of the population. This can be problematic when your research results are meant to be generalizable to the population at large. However, surveyors typically know the true proportion of demographic traits among the U.S. population, and provide survey weights that compensates for their sampling bias, by increasing the importance of underrepresented groups in individual's statistical analyses. In this problem, we will practice using survey weights.

The American film studio, Delimited Pictures, is interested in how many tickets they should expect to sell to adults for their upcoming film, Cambrian Park, and what age group are most likely to watch it. They interview people across the country, asking them whether they plan to see the movie when it comes out. Although their resulting sample was not perfectly representative of the country's adult population, a statistician was able to provide them with survey weights that compensate for this sampling error. Use these survey weights and the dataset Survey to help Delimited Pictures estimate what proportion of the U.S. adult population will see their upcoming movie, and to determine what age group is most likely to watch it.

Instructions

100 XP
  • 1) Get a sense of survey weights by summarizing the dataframe Survey.
  • 2) Look through the following example of how survey weights can compensate for unrepresentative sampling.
  • 3) Estimate the proportion of the US adult population that plans to watch Cambrian Park (variable WillWatch) while using the provided survey weights.