y = (t x - m -s)/r
Step-by-step explanation:
Step 1 :
Given,
r y + s = t x - m
=> r y = t x - m -s
=> y = (t x - m -s)/r
Step 2 :
A) r can take any values except 0.
This is because when r = 0, the denominator becomes 0 and division by 0 is undefined
The limitation for r is r should not be equal to 0
The other variables can take any value. Hence the other variables do not have any limitation
<h3>
Answer: Choice E</h3>
======================================================
Explanation:
Think of 25 as 25/1 and 5 as 5/1
Choice E is really saying 
which becomes 
. Note the second fraction flips and we change to a multiplication sign.
------------
Or you could think of it like this:
to help see why the answer is E.
Answer:
4
Step-by-step explanation:
1 x 24
2 x 12
3 x 8
4 x 6
Answer:
52
Step-by-step explanation:
When asked such a question, try to use trial and error.
For example, the total is 202 and is made of of 4 integers which are <u>consecutive</u>(follow each other)
If you were to divide 202 by 4, you would get approximately 50
So, it would be best to try and add certain consecutive numbers(making sure 50 is one of them) till you get a total of 202
In this case, the integers would be, <em>49, 50, 51</em> and <em>52</em>
The question then further asks you ti find out which is the greatest of these integers. That would be <em>52</em>
Answer:
Option A is right
Step-by-step explanation:
Given that approximately 52% of all recent births were boys. In a simple random sample of 100 recent births, 49 were boys and 51 were girls. The most likely explanation for the difference between the observed results and the expected results in this case is
A) variability due to sampling
-- True because there is a slight difference whichmay be due to sampling fluctuations.
B) bias
False because given that 100 random births selected
C) nonsampling error
False. There is no chance for systematic error here.
d) Confounding: There is no confounding variable present inchild birth since each is independent of the other
e) a sampling frame that is incomplete
False because the sampling is done correctly.
