How to use normalization to set levels of confidence between a rating and the number of ratings in P

Certainly! Normalization is a crucial technique in data analysis to standardize or scale values, making them comparable across different scales. In the context of setting levels of confidence between a rating and the number of ratings, normalization helps ensure that both factors contribute appropriately to the overall assessment. In this tutorial, we'll explore how to use normalization in both Python and SQL to achieve this.
Now, ConfidenceScore will be the normalized combination of rating and the number of ratings.
Assuming you have a table named RatingTable with columns Rating and NumRatings.
In this SQL example, we use a temporary table to store the normalized values for both Rating and NumRatings. The final query then calculates the confidence score using the normalized values.
By following these steps, you can effectively use normalization to set levels of confidence between a rating and the number of ratings, ensuring a fair and balanced representation of the data.
ChatGPT