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Sholpan [36]
3 years ago
15

Binomial Probability Distribution. How to determine the probability of one candidate of two winning.

Mathematics
1 answer:
Angelina_Jolie [31]3 years ago
4 0
.5

B - binary?
I - independent?
N - trials
S - prob success

B - yes, win or not
I - past candidates don’t affect future candidates
N - 2 candidates
S - .5 probability of winning

Go to the binompdf function on your graphing calculator.

binompdf(2 (trials), .5 (p), 1 (1)) = .5
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A 26' Long painting is how many yards Long
Alenkinab [10]
In one foot, there are 0.33 yards.
Therefore, you need to multiply 26 by 0.33
20x0.33= 6.6
6x0.33= 1.98 yards.
6.6+1.98= 8.58
Therefore, in a 26' long painting, there are 8.58 yards
Hope this helps :) 
3 0
3 years ago
Read 2 more answers
Amanda's family is taking a road trip. Their car can travel no more than 352 miles without needing to refill the gas tank. They
Solnce55 [7]

From the solution to the inequality, the correct interpretation is that:

Amanda's family can drive 244 miles before they need to refill the gas tank.

The amount of miles they can still travel is modeled by the following <em>inequality</em>:

108 + x \leq 352

It is solved similarly to an equality, hence:

x \leq 352 - 108

x \leq 244

Then:

Amanda's family can drive 244 miles before they need to refill the gas tank.

You can learn more about inequalities at brainly.com/question/25629776

6 0
2 years ago
VE
Firdavs [7]

Answer:

$4167

Step-by-step explanation:

Original Amount: $4167 (rounded)

First Year: $4167 + $416.7 = $4583.7

Second Year $4583.7 + $416.7 = 5000.4

8 0
3 years ago
The director of admissions at Kinzua University in Nova Scotia estimated the distribution of student admissions for the fall sem
wariber [46]

Answer:

In order to calculate the expected value we can use the following formula:  

E(X)=\sum_{i=1}^n X_i P(X_i)  

And if we use the values obtained we got:  

E(X)=(1060*0.5) +(1400*0.1) +(1620*0.4)=1318  

Step-by-step explanation:

Let X the random variable that represent the number of admisions at the universit, and we have this probability distribution given:

X        1060   1400    1620

P(X)     0.5      0.1        0.4

In statistics and probability analysis, the expected value "is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values".

The variance of a random variable Var(X) is the expected value of the squared deviation from the mean of X, E(X).

And the standard deviation of a random variable X is just the square root of the variance.  

In order to calculate the expected value we can use the following formula:  

E(X)=\sum_{i=1}^n X_i P(X_i)  

And if we use the values obtained we got:  

E(X)=(1060*0.5) +(1400*0.1) +(1620*0.4)=1318  

3 0
3 years ago
A possible graph transformation f(kx) when 0 &lt; k &lt; 1 is?
Nitella [24]

Answer:

rgvrgvtgbrgvrgbthrfvrgvrhgbthgrvgvrgvthbtrfvrgvrgvhtbvrgvrgvhbt

Step-by-step explanation:

7 0
3 years ago
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