A box has colored balls (12 red, 10 green, 6 light blue and 8 yellow). What is the probability of drawing 2 red balls?
1 answer:
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Probability would been equal to 0.9841 if we randomly select 20 bottles it fills.
<h3>What is Probability ?</h3>The ratio of good outcomes to all possible outcomes of an event is known as the probability. The number of the positive results for the experiment with 'n' outcomes can also be represented by the symbol x. The probability of an event can be calculated using the following formula.
Probability(Event) = Positive Results/Total Results = x/n
Given,
n = 20
p = 0.05
Thia information gives information about binomial distribution with parameter n = 20 , p = 0.05
Let X be the number of bottles have caps that she not properly applied
X∝ B( n=20 , p= 0.05)
The p.m.f of X is
P( X=0)= () ( 0.05)ˣ (1 - 0.05)²⁰ ⁻ˣ
; x = 0 , 1, 2.......20
0 < p < 1
q= 1 - p
= 0 ; otherwise
P {x ≤ 3} = P { X = 0 } + P{ x= 1 } + P { x= 2 } + P { x= 3}
P( X=0)= () ( 0.05)⁰ (1 - 0.05)²⁰ ⁻⁰ = 0.3585
P( X = 1)= 0.3774
P( X= 2) = 0.1887
P( X= 3) = 0.0596
= 0.3585+ 0.3774 + 0.1887+ 0.0596
= 0.9841
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Answer:
Now we can calculate the p value with this probability:
If we use a significance level os 0.05 we see that the p value is lower than the significance level so then we can conclude that the true proportion of students with jobs is higher than 0.35 for this case. If we decrease the significance level to 1% the result changes otherwise not.
Step-by-step explanation:
Information given
n=78 represent the random sample taken
X=36 represent the students with jobs
estimated proportion of students with jobs
is the value that we want to test
z would represent the statistic
represent the p value
Hypothesis to test
We want to test if the proportion of students with jobs is higher than 0.35, the system of hypothesis are:
Null hypothesis:
Alternative hypothesis:
The statistic is given by:
(1)
Replacing the info we got:
Now we can calculate the p value with this probability:
If we use a significance level os 0.05 we see that the p value is lower than the significance level so then we can conclude that the true proportion of students with jobs is higher than 0.35 for this case. If we decrease the significance level to 1% the result changes otherwise not.