Answer:
Hence the probability that she paid cash is 0.105
Step-by-step explanation:
P(cash) = 0.3
P(credit card ) = 0.3
P(debit card ) = 0.4
P ( more than $50 | cash ) = 0.2
P (more than $50 | credit card ) =0.9
P (more than $ 50 |debit card ) = 0.6
P ( more than $50) = P ( more than $50 | cash )* P (cash) + P (more than $50 credit card ) * P(credit card ) + P (more than $ 50 |debit card )* P(debit card )
= 0.2 * 0.3 + 0.9 * 0.3 + 0.6* 0.4
= 0.57
P ( more than $50) = P ( more than $50 | cash )* P (cash) / P ( more than $50)
= 0.2* 0.3 / 0.57
= 0.105
Answer: y+6x = -34
<em><u>Step-by-step explanation:</u></em>
y-2= -6(x+6) (<u><em>Ax+By=C is the goal)</em></u>
y-2= -6x-36 <u>(-6) x & (-6) 6</u>
y=-6x-34 (Add 2 to both sides)
<em>y+6x = -34 [Add 6x to both sides]</em>
Answer:
3,-3
Step-by-step explanation:
g(3)= (3)³+6(3)²-9(3)-54
= 27+54-27-54
=81-81
= 0
g(-3) = (-3)³+6(-3)²-9(-3)-54
= -27+54+27-54
= 27-27
= 0
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Answer:
0.2
Step-by-step explanation:
Given the data :
Day : Mon Tue Wed Thu Fri Sat Sun
# of sick days 22 11 16 17 21 28 25
The expected count of sick days taken on Saturday is obtained thus :
Expected count = (row total * column total) / overall total
Here, the table is just one way :
Hence, we use :
Observed value / total days
Hence,
Expected count on Saturday = sick days on Saturday / total sick days
Expected count on Saturday = 28 / (22+11+16+17+21+28+25)
Expected count on Saturday = 28 / 140
= 0.2
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