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M6_STARTUP_PREDICTION

M6_STARTUP_PREDICTION

M6_STARTUP_PREDICTION synthetic teaching data for Module 6 prediction, nonnested comparison, and prediction intervals.

Download CSV

Structure

other

File type

CSV

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 M6_STARTUP_PREDICTION from the dataset link first.
data = pd.read_stata("M6_STARTUP_PREDICTION.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

revenuenumeric

revenue used for Module 6 prediction, nonnested comparison, and prediction intervals.

Missing values: Review source documentation before recoding missing values.

lrevenuenumeric

lrevenue used for Module 6 prediction, nonnested comparison, and prediction intervals.

Missing values: Review source documentation before recoding missing values.

team_sizenumeric

team_size used for Module 6 prediction, nonnested comparison, and prediction intervals.

Missing values: Review source documentation before recoding missing values.

capitalnumeric

capital used for Module 6 prediction, nonnested comparison, and prediction intervals.

Missing values: Review source documentation before recoding missing values.

product_agenumeric

product_age used for Module 6 prediction, nonnested comparison, and prediction intervals.

Missing values: Review source documentation before recoding missing values.

mentornumeric

mentor used for Module 6 prediction, nonnested comparison, and prediction intervals.

Missing values: Review source documentation before recoding missing values.

Practice tasks

  1. 1.M6_STARTUP_PREDICTION is catalogued for Module 6 prediction, nonnested comparison, and prediction intervals. Open the linked Drive source to install the file before validating output.
  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.