Back to datasets

SLEEP75

SLEEP75

SLEEP75 installed course data for Module 8 group variance and time-use regression examples.

Download DTA

Structure

cross-sectional

File type

DTA

Module

Course catalog

Visibility

public

Preview table

Preview rows are shown when safely installed in the app. External or licensed files may need to be opened from the source link.

No local preview table is installed for this dataset. Use the download/source link, then load it with the Python example below.

Python loading code

import pandas as pd

# Download SLEEP75 from the dataset link first.
data = pd.read_stata("SLEEP75.DTA")
print(data.head())

Check the variable dictionary and source documentation before dropping or recoding missing values.

Dataset AI assistant

Get help with variables, graphs, regression questions, limitations, and Python loading code.

Variables dictionary

sleepnumeric

sleep used for Module 8 group variance and time-use regression examples.

Missing values: Review source documentation before recoding missing values.

totwrknumeric

totwrk used for Module 8 group variance and time-use regression examples.

Missing values: Review source documentation before recoding missing values.

educnumeric

educ used for Module 8 group variance and time-use regression examples.

Missing values: Review source documentation before recoding missing values.

agenumeric

age used for Module 8 group variance and time-use regression examples.

Missing values: Review source documentation before recoding missing values.

malenumeric

male used for Module 8 group variance and time-use regression examples.

Missing values: Review source documentation before recoding missing values.

Practice tasks

  1. 1.SLEEP75 is catalogued for Module 8 group variance and time-use regression examples. Installed data file; synthetic files are original practice data, and course files require license verification before public download.
  2. 2.Create one summary table and one graph that support an econometric question.
  3. 3.Write one limitation about measurement, missing data, or omitted variables.