R Tutorial: What are survey weights?

Want to learn more? Take the full course at https://learn.datacamp.com/courses/analyzing-survey-data-in-r at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Hi! I am Kelly McConville, a survey statistician, and professor. Welcome to my course on analyzing survey data. Now I am wondering if you have ever found yourself in the following situation: You have a question you want to answer. You found a great dataset to answer that question and then there’s this column in the dataset that represents survey weights. And you ask yourself: What are those? Can I ignore those? Well, let’s pretend we have found ourselves in this situation. We want to estimate the average household income in the US. We find that the Bureau of Labor Statistics provides a public use dataset. And, this dataset includes the variable FINCBTAX, given in the second column here, which is the amount of household income before taxes in 2016. But the first column in the dataset is a survey weight variable, FINLWT21. How should these weights impact our analyses? First, we should ask: what are survey weights? Survey weights result from data that were collected under a complex sampling design. The weights tell us the number of individuals in the population that each sampled individual represents. Returning to the BLS sample, the first weight equals 25,985, which means that the first sampled household in the dataset represents 25,985 households in the population. The second represents 6,581 households. Now that we know what survey weights are, the question remains: How will they impact our analyses? Let’s consider a common goal for survey data: to estimate a population quantity. Suppose this picture reflects all households in the US where each green box is an individual household. And we want to estimate the average household income. Then y_i is the income for the ith household, U represents all US households, and capital N is the