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GPA2

GPA2

GPA2 installed course data for Module 7 student group indicators and controlled academic comparisons.

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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 GPA2 from the dataset link first.
data = pd.read_stata("GPA2.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

colgpanumeric

colgpa used for Module 7 student group indicators and controlled academic comparisons.

Missing values: Review source documentation before recoding missing values.

satnumeric

sat used for Module 7 student group indicators and controlled academic comparisons.

Missing values: Review source documentation before recoding missing values.

hspercnumeric

hsperc used for Module 7 student group indicators and controlled academic comparisons.

Missing values: Review source documentation before recoding missing values.

femalenumeric

female used for Module 7 student group indicators and controlled academic comparisons.

Missing values: Review source documentation before recoding missing values.

athletenumeric

athlete used for Module 7 student group indicators and controlled academic comparisons.

Missing values: Review source documentation before recoding missing values.

Practice tasks

  1. 1.GPA2 is catalogued for Module 7 student group indicators and controlled academic comparisons. Installed original synthetic CSV; estimates are practice results, not real empirical findings.
  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.