Minimizing the sum of the squared deviations around the line is called Least square estimation.
It is given that the sum of squares is around the line.
Least squares estimations minimize the sum of squared deviations around the estimated regression function. It is between observed data, on the one hand, and their expected values on the other. This is called least squares estimation because it gives the least value for the sum of squared errors. Finding the best estimates of the coefficients is often called “fitting” the model to the data, or sometimes “learning” or “training” the model.
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Answer:
What are the answer options... I have an answer but I want to check if it is correct... thanks
Step-by-step explanation:
6. 5. That’s the answer hope it helps
Hey there!
To start, the mean of the answer is also known as the average value of a set of numbers. This is calculated by dividing the sum of the set by the total amount of numbers.
In this case the sum of all the numbers is 13 + 6 + 8 + 6 + 15 which is equal to 48.
Now, divide 48 by the total number of numbers in the set: 48/5 = 9.6
Your final answer should be 9.6, or you can leave it in fraction form as 48/5.
Hope this helps!
$2.86 if you’re tipping off of $19.06 but if you’re tipping off half of that so the split bill which is $9.53 then your tip is $1.43
