Let's say you want to compute the probability

where

converges in distribution to

, and

follows a normal distribution. The normal approximation (without the continuity correction) basically involves choosing

such that its mean and variance are the same as those for

.
Example: If

is binomially distributed with

and

, then

has mean

and variance

. So you can approximate a probability in terms of

with a probability in terms of

:

where

follows the standard normal distribution.
vertex (1,-1) axis of symmetry is x=1, domain all real numbers (i think neg ys) range y is less equal than -1, y increases as x less 0 bug IMO x decreases
1. Definition of bisector
2. ASA congruence theorem or ASA Postulate
Answer:

Step-by-step explanation:






<u>FINAL ANSWER</u>

<u><em>In Decimal Form (Rounded to 3 significant figures)</em></u>
<em>x≈-1.24, 3.24</em>
Answer:
508
Step-by-step explanation:
28*16= 448
6*6= 36
4*6= 24
448+36+24= 508