Question 1

Applicable packages and libraries were imported.

• Yes ✅

• No ❌

Explanation:
A proper project includes imports such as pandas, numpy, matplotlib, seaborn, sklearn (if applicable), etc.

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Question 2

head() function was used to analyze the data.

• Yes ✅

• No ❌

Explanation:
head() is required to inspect the first rows of the dataset.

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Question 3

info() function was used to analyze the data.

• Yes ✅

• No ❌

Explanation:
info() verifies datatypes and missing values — required for analysis.

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Question 4

describe() function was used to analyze the data.

• Yes ✅

• No ❌

Explanation:
describe() provides summary statistics and must be included.

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Question 5

All questions in the code notebook were answered.

• Yes ✅

• No ❌

Explanation:
Completing all notebook questions ensures full evaluation credit.

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Question 6

All questions in the PACE strategy document were answered.

• Yes ✅

• No ❌

Explanation:
The PACE document must be fully filled out to earn this point.

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Question 7

Executive summary mentioned the tasks completed in the project.

• Yes ✅

• No ❌

Explanation:
A good executive summary must reference the workflow and activities performed.

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Question 8

Executive summary included information about the data variable assessment.

• Yes ✅

• No ❌

Explanation:
Your summary must describe the quality and results of your variable evaluation.

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Question 9

Executive summary identified recommended next steps to build a predictive model.

• Yes ✅

• No ❌

Explanation:
The summary must propose next steps such as feature engineering, model building, validation, etc.

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🧾 Summary Table

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