Which function best models the data? The table shows the estimated number of bees, y, in a hive x
days after a pesticide is released near the hive.
Bee Population over Time
O y = 9,958(0.972)*
y = 0.972(9,958)*
O y = 9,219x, 150
O y = -150x + 9,219
Number of days
0
10
20
30
40
50
Estimated number of bees
10.000
7.500
5.600
4,200
3,200
2.400

y = 9,958(0.972)^t

Step-by-step explanation:

From point to point, the difference in days is always constant (10 days), but the difference between estimated number of bees is not constant.

10000  - 7500  = 2500

7500  - 5600  = 1900

5600  - 4200  = 1600

4200  - 3200  = 1000

3200  - 2400 = 800

Therefore, the data don't fit a line.

From the other two options:

y = 9,958(0.972)^t

y = 0.972(9,958)^t

only the first one has sense, because its initial amount of bees is 9,958 (near to 10,000) and in the second option is 0.972.

step-by-step explanation:

the original amount doesn't ''re just looking for the time it takes for 1/2 of the substance to we have

(1/2) =)     take the ln   of both sides

ln (1/2)   = )   and we can write

ln(1/2) = ) lne     and lne   = 1     so we have

ln(1/2) = -.1092t     divide both sides by -.1092

t = ln(1/2)/-.1092 = about 6.347 days = about 6.3 days (rounded)

0.16 or 16%

step-by-step explanation:

lets take a coin for example.

if you toss it twice, it has a 1/4 chance of landing on heads both times because 1/2 * 1/2 is 1/4.

with the cards, the chance of picking dog is 0.4. having two people pick one is like picking a card twice in a row. so 0.4 * 0.4 is 0.16, or 16%