We have been given that a graph that represents the amount of money in dollars that Tony expects to deposit in his account in terms of the number of years since opening the account.
We are asked to find the rate of change and initial value from our given graph.
We know that initial value is the point, where, graph intersects y-axis that is when x is equal to 0.
We can see that graph starts at 5000 on y-axis, therefore, initial value is $5000.
The rate of change will be equal to slope of line. Let us find slope of line using points (0,5000) and (1,7500).
Therefore, the rate of change is $2500 per year.
The equation 
represents the amount of money in dollars that Tony expects to deposit in his account.
In this item, it can be seen that from an expression of,
(4 + 5i) + (-3 + 7i)
Aiko transformed the equation by factoring out the i's from the expression and wrote it as,
(4 + 5)i + (-3 + 7)i
Now this is wrong because i there is not a variable but a notation that 5 and 7 are imaginary numbers. In fact, she cannot factor out the i's because it is not present in both -3 and 4. The answer therefore to this item is the last sentence, "Aiko incorrectly used the distributive property by combining ..."
<h2>Answer:</h2>
m∠A = mDE - mBC
x° = 116° - 64°
x° = 52°.
Therefore, m∠A equal to 52°.
<u>Correct choice</u> - [D] 52°.
The data below shows the average number of text messages sent daily by a group of people: 7, 8, 4, 7, 5, 2, 5, 4, 5, 7, 4, 8, 2,
enot [183]
It all depends. You've given us an incredibly vague question.
The outlier could be a number that's low or quite high. Also, outliers
shouldn't really contribute towards the value of the mean, median or
range related to a group of data.
They are called outliers because they are bizarre results or numbers
and should be detached from groups of data. Outliers by definition
are abnormalities or anomalies.
I'd say outliers don't really change anything, unless you actually want
to give them credibility or weight.
Large outliers can inflate the value of means, medians and ranges.
Small outliers will invariably deflate the value of means and medians.
