Answer:
II. The sum of the residuals is always 0.
Step-by-step explanation:
A least squares regression line is a standard technique in regression analysis used to make the vertical distance obtained from the data points running to the regression line to become very minimal or as small as possible.
For any least-squares regression line, the sum of the residuals is always zero.
Basically, residuals are used to measure or determine whether or not the line of regression is a good fit or match for the data by subtracting the difference between them i.e the predicted y value and the actual y value, for the x value respectively.
Hence, the statement about residuals which is true for the least-squares regression line is that the sum of the residuals is always zero (0).
Answer: the answer is B (0,7)
I got I right 100%
Answer: probability = 0.506
Step-by-step explanation:
The data we have is:
Total people: 205 + 160 + 40 = 405
prefer cats: 205
prefer dogs: 160
neither: 40
The probability that a person chosen at random prefers cats is equal to the number of people that prefer cats divided the total number of people:
p = 205/405 = 0.506
in percent form, this is 50.6%
Answer:
4/3
Step-by-step explanation:
12x-9y=-9
9y=12x-(-9)
9y=12x+9
y=12/9x+9/9
y=4/3x+1
y=mx+b where m=slope and b=y-intercept,
so the slope is 4/3
Answer:
I needed thisssss ! Thanks for the points and you too<3
Step-by-step explanation:
