Count the number of 1 bits after the last decimal point. Call this number n.
There will be 2^n subnets and 2^(8-n) - 2 hosts per subnet. (You can mutilply the number of subnets by the number of hosts per subnet to find the total number of hosts.)
/25: 255.255.255.128, 2 subnets, 126 hosts per subnet
/26: 255.255.255.192, 4 subnets, 62 hosts per subnet
/27: 255.255.255.224, 8 subnets, 30 hosts per subnet
/28: 255.255.255.240, 16 subnets, 14 hosts per subnet
/29: 255.255.255.248, 32 subnets, 6 hosts per subnet
Which characteristic of a data set makes a linear regression model unreasonable?
Answer: A correlation coefficient close to zero makes a linear regression model unreasonable.
If the correlation between the two variable is close to zero, we can not expect one variable explaining the variation in other variable. For a linear regression model to be reasonable, the most important check is to see whether the two variables are correlated. If there is correlation between the two variable, we can think of regression analysis and if there is no correlation between the two variable, it does not make sense to apply regression analysis.
Therefore, if the correlation coefficient is close to zero, the linear regression model would be unreasonable.
Plot 7 on the y axis then go down 4 places and left 1 and keep repeating till u can’t plot any more then go back to the 7 on the y axis and go up 4 and right 1 unroll you can’t plot any more. Your line should be going down from left to right
I think that it's B, y = -x - 7 because first you'd subtract y to get it on the other side then add x and then you'd need to make the y positive so you would divide x + 7 by -1 and that would make it y = -x - 7.
