This Multiple Regression lesson is for a beginner. Read the short notes, run each example, then change one name or number and run it again.
Multiple regression uses more than one input column to predict one target.
Hours studied and hours slept can both help predict a score. Each column gets its own weight.
Example 1: Start here
Each tuple is hours, sleep, and score. The score is the target.
rows = [(2, 7, 60), (4, 6, 70), (6, 8, 85)] # a list; the values stay in this order
print([row[2] for row in rows]) # in is True when the value is found
Example 2: Add two rows
Multiple Regression applies one operation to every number. zip pairs the rows, and the list keeps each sum.
left = [1, 2, 34] # a list; the values stay in this order
right = [10, 20, 30] # a list; the values stay in this order
print([a + b for a, b in zip(left, right)]) # pair the lists, then combine each pair
Example 3: Average a column
The average is the total divided by how many numbers you have. That is the same summary a statistics page starts with.
scores = [70, 34, 90] # a list; the values stay in this order
print(sum(scores) / len(scores)) # len counts the items
Example 4: Keep values above a line
A cutoff drops the low values. Change 80 and run the example again to see who remains.
scores = [70, 34, 90] # a list; the values stay in this order
print([score for score in scores if score >= 80]) # keep the items that pass the test
Each tuple is hours, sleep, and score. The score is the target.
