Module 6

Log Prediction and Smearing

Compare naive and smearing-adjusted retransformation from log outcomes.

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Notebook lab guide

Related dataset

M6_HOUSING_LOGS

Estimated time

25 to 40 min

Packages

pandas, numpy

Expected output

Printed Python results that can be compared with the lesson explanation.

Learning goals

Load and inspect M6_HOUSING_LOGS.
Run the Python cells connected to Predictions when the Dependent Variable Is Logged.
Interpret the output using log prediction and smearing.

Common errors

File not found: check that M6_HOUSING_LOGS.csv is installed or use the course data folder.
Package import error: use the browser notebook first, then download for local Jupyter if your local packages differ.
Column name error: compare your variable names with the dataset variables listed for this notebook.

Dataset path helper

import pandas as pd

df = pd.read_csv("/data/module-6/M6_HOUSING_LOGS.csv")
df.head()

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