Flash cards
Review the key moves
1/4
Core idea
What is the main idea behind Data Science - Regression Table - Coefficients?
Lesson checks
Practice each idea before moving on
Short Mimo-style checks built from this lesson's code, terms, and sequence.
1Quick choice
Which statement best captures the main point of this lesson?
2Fill blank
Complete the missing token from the example code.
___ = 0.3296 * Average_Pulse + 346.86623Order
Put the learning moves in the order that makes the concept easiest to apply.
- Coef is short for coefficient.
Define the Linear Regression Function in Python
The "Coefficients Part" in Regression Table
4Data move
Before charting or modeling a dataset, which move should come first?
The "Coefficients Part" in Regression Table
- Coef is short for coefficient. It is the output of the linear regression function.
The linear regression function can be rewritten mathematically as:
Calorie_Burnage = 0.3296 * Average_Pulse + 346.8662These numbers means
- If Average_Pulse increases by 1, Calorie_Burnage increases by 0.3296 (or 0,3 rounded)
- If Average_Pulse = 0, the Calorie_Burnage is equal to 346.8662 (or 346.9 rounded).
- Remember that the intercept is used to adjust the model's precision of predicting!
Do you think that this is a good model?
Define the Linear Regression Function in Python
Define the linear regression function in Python to perform predictions.
What is Calorie_Burnage if Average_Pulse is: 120, 130, 150, 180?
Example
def Predict_Calorie_Burnage(Average_Pulse):
return(0.3296*Average_Pulse +
346.8662)
print(Predict_Calorie_Burnage(120))
print(Predict_Calorie_Burnage(130))
print(Predict_Calorie_Burnage(150))
print(Predict_Calorie_Burnage(180))