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CRIME1

CRIME1

CRIME1 installed course data for Module 8 robust LM tests and discrete arrest outcome cautions.

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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 CRIME1 from the dataset link first.
data = pd.read_stata("CRIME1.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

narr86numeric

narr86 used for Module 8 robust LM tests and discrete arrest outcome cautions.

Missing values: Review source documentation before recoding missing values.

pcnvnumeric

pcnv used for Module 8 robust LM tests and discrete arrest outcome cautions.

Missing values: Review source documentation before recoding missing values.

avgsennumeric

avgsen used for Module 8 robust LM tests and discrete arrest outcome cautions.

Missing values: Review source documentation before recoding missing values.

ptime86numeric

ptime86 used for Module 8 robust LM tests and discrete arrest outcome cautions.

Missing values: Review source documentation before recoding missing values.

qemp86numeric

qemp86 used for Module 8 robust LM tests and discrete arrest outcome cautions.

Missing values: Review source documentation before recoding missing values.

Practice tasks

  1. 1.CRIME1 is catalogued for Module 8 robust LM tests and discrete arrest outcome cautions. 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.