30.4.1. Data Collection and Preprocessing

Try these first

1. 1.

   What is data cleaning?

   Hint

   Think about why we need accurate data for analysis.

2. 2.

   Why is normalization needed?

   Hint

   Consider how different units can affect calculations.

3. 3.

   What is the primary goal of data cleaning?

   • To analyze the data
   • To correct inaccuracies
   • To add new data

   Hint

   Remember the importance of accurate data for reliable analysis.

4. 4.

   True or False: Normalization is unnecessary if all data is already on a similar scale.

   • True
   • False

   Hint

   Think about data representation in machine learning models.

5. 5.

   Given a dataset with missing values, describe two different methods you could use to address the issue, including the potential consequences of each approach.

   Hint

   Think about the trade-offs between data integrity and accuracy in predictions.

6. 6.

   Imagine you have collected sensor data with significant outliers due to equipment malfunction. How would you identify and handle these outliers in your preprocessing steps?

   Hint

   Consider how outliers can skew the results in statistical analyses.