To solve this equation , we need to write it in quadratic form
To get the equation in quadratic form we replace x^2 with u
can be written as
, Replace u for x^2
So equation becomes
Now we factor the left hand side
-16 and -1 are the two factors whose product is +16 and sum is -17
(u-16) (u-1) = 0
u -16 = 0 so u=16
u-1 =0 so u=1
WE assume u = x^2, Now we replace u with x^2
Now take square root on both sides , x= +4 and x=-4
Now take square root on both sides , x= +1 and x=-1
So zeros of the function are -4, -1, 1, 4
Answer:
2,436 students
Step-by-step explanation:
At a 90% confidence level, the z-score is 1.645 and the confidence interval is given by:
Where s is the standard deviation, and n is the sample size.
If they want the length of their confidence interval to be no greater than 0.2, it must be no further than 0.1 from the mean 'X':
Rounding up to the next whole number, the sample size should be 2,436 students.
Answer:
4
Step-by-step explanation:
(5x + 4y = 8) 2 = 10x+8y=16
(2x - 3y = 17)5 = 10x-15y=85
we can pick one of the equation and multiply it by a -1 which equals:
10x+8y=16
-10x+15y=-85
and -10 and 10 cancels out.
add 8 and 15 = 23y
add -85 and 16 = -69
divide -69 by 23 whcih equals -3
plug in the y value in any of the equation, i chose 2x - 3y = 17
you get 2x+9=17
2x=8
x=4
Answer:
The answer is Option E; both B and C are correct
Step-by-step explanation:
Both (b) and (c) are correct. Simpson's paradox is a paradox in which a trend that appears in different groups of data disappears when these groups are combined, and the reverse trend appears for the aggregate data. This result is often encountered in social-science and medical-science statistics, and is particularly confounding when frequency data are unduly given causal interpretations. Simpson's Paradox disappears when causal relations are brought into consideration.
Now, this question is an example of Simpsons paradox because the groups of collected data over a period of time from five major cities showed a trend that StatsAir does better overall, but this trend is reversed when the groups are studied separately to show that air median does better.
So, option B is correct.
Also, City is a variable that influences both the dependent variable and independent variable, causing a spurious association. That is it is the cause of why the 2 results are biased. Thus, city is a lurking variable.
So, option C is also correct
The first option is correct. See an explanation below.
