{"part":"task","text":"# Datasets\nPass a dataset's id as the `dataset` argument.\n{\n \"id\": \"ak91\",\n \"rows\": 329509,\n \"description\": \"The dataset provided, ak91.csv, contains information on individuals' log wages, years of schooling, year of birth, quarter of birth, and state of birth. The purpose of the analysis is to estimate the effect of education on wage, using linear regression and quarter of birth as an instrumental variable (IV). This idea takes advantage of US compulsory attendance law. Usually, they state that a kid must have turned 6 years by January 1 of the year they enter school. For this reason, kids that are born at the beginning of the year will enter school at an older age. Compulsory attendance law also requires students to be in school until they turn 16, at which point they are legally allowed to drop out. The result is that people born later in the year have, on average, more years of education than those born in the beginning of the year.\",\n \"columns\": {\n  \"log_wage\": \"float64\",\n  \"years_of_schooling\": \"float64\",\n  \"year_of_birth\": \"float64\",\n  \"quarter_of_birth\": \"float64\",\n  \"state_of_birth\": \"float64\"\n }\n}"}