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LOANAPP

LOANAPP

LOANAPP unavailable course data for Module 8 loan approval LPM and robust confidence intervals.

Open LINK data

Structure

cross-sectional

File type

LINK

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

approvenumeric

approve used for Module 8 loan approval LPM and robust confidence intervals.

Missing values: Review source documentation before recoding missing values.

whitenumeric

white used for Module 8 loan approval LPM and robust confidence intervals.

Missing values: Review source documentation before recoding missing values.

hratnumeric

hrat used for Module 8 loan approval LPM and robust confidence intervals.

Missing values: Review source documentation before recoding missing values.

obratnumeric

obrat used for Module 8 loan approval LPM and robust confidence intervals.

Missing values: Review source documentation before recoding missing values.

loanprcnumeric

loanprc used for Module 8 loan approval LPM and robust confidence intervals.

Missing values: Review source documentation before recoding missing values.

unemnumeric

unem used for Module 8 loan approval LPM and robust confidence intervals.

Missing values: Review source documentation before recoding missing values.

Practice tasks

  1. 1.LOANAPP is catalogued for Module 8 loan approval LPM and robust confidence intervals. Dataset not installed yet; use the course data folder to locate and install this file.
  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.