Answer:
zero(0)
Step-by-step explanation:
The additive identity of a set of number is a number such that the its sum with any of the numbers in the set would give a result that is equal to the number in that set.
In other words, say for example the set of numbers is rational, the additive identity of rational numbers is 0. This is because, given any rational number say <em>x</em>, adding zero to the number <em>x</em> gives the same number <em>x. </em>i.e
x + 0 = x
If x is say 2, then we have;
2 + 0 = 2
Since adding zero to rational numbers gives has no effect on the numbers, then zero (0) is the additive identity of rational numbers.
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2a+4(7+5a)
Distribute 4 into 7 and 5a
2a+28+20a
Combine like terms
Final Answer: 22a+28
Answer:
A.
Negative reciprocal gives you the perpendicular slope so negative reciprocal of 1/2 is -2.
Then apply point-slope form.
B. The answer is x = 6.
The midpoint of JK is
The line that goes through JK is just a horizontal line 
because the y-coordinate does not change. So its perpendicular bisector is the vertical line that goes through the x-coordinate of the midpoint, that is, 
.
Answer:
No, the Roger’s claim is not correct.
Step-by-step explanation:
We are given that Roger claims that the two statistics most likely to change greatly when an outlier is added to a small data set are the mean and the median.
This statement by Roger is incorrect because the median is unaffected by the outlier value and only the mean value gets affected by the outlier value.
As the median represents the middlemost value of our dataset, so any value which is an outlier will be either at the start or at the end will not the median value. So, the median will not likely change when an outlier is added to a small data set.
Now, the mean is the average of all the data set values, that is the sum of all the observations divided by the number of observations. The mean will get affected by the outlier value because it take into account each and every value of the data set.
Hence, the mean will likely to change greatly when an outlier is added to a small data set.
Answer:
4
a=k/b squared when a=1,b=4 k=16
When b=4 a=1
