Answer: D. minimizes the sum of the squared residuals
Step-by-step explanation: The ordinary least square method is often used in locating the trendine which best fits a graphical linear model. The best is one in which the sum of the squared residual is smallest. The residual refers to the difference between the actual and the predicted points. The sum of the squared differences is obtained and the trend line is positioned where the residual is minimum. Choosing a OLS, and minimizing the sum.of the squared residual, the error difference between the predicted and actual score is minimized or reduced, hence, improving the prediction accuracy of our model.
Answer:
C (reflection across the x access)
Step-by-step explanation:
I got it right on edge
Step-by-step explanation:
first fish tank: 95-4x
second fish tank: 40+5x
1. Define variable
The variable x represents the number of days.
2. Write the inequality
<em>95-4x=40+5x</em>
<em />
3. You probably don't need the answer but I am just going to solve.
The first fish tank will have less water than the second fish tank after 7 days.
<em>95-4x=40+5x </em>
<em>95-4(7)=40+5(7)</em>
<em>95-28=40+35</em>
<em>67=75</em>
<em>Since the first equation (95-4x) represents the first fish tank, and the second equation (40+5x) represents the second fish tank, the solution shows how the amount of water in the first fish tank is less than the amount of water un the second fish tank after 7 days.</em>
Actually, yes, it is possible for two different numbers to give the same result when squared.
In my last answer, I wrote that it wasn't, but I realize now where my mistake was made.
When a number like positive 4 is squared, the answer is 16. When a number like negative 4 is squared, the answer is also 16. I think that the only time when two different squared numbers have the same result is when they are the same number but have a different positive/negative sign.
I hope this helps.
