Answer:
The probability of getting a sample with 80% satisfied customers or less is 0.0125.
Step-by-step explanation:
We are given that the results of 1000 simulations, each simulating a sample of 80 customers, assuming there are 90 percent satisfied customers.
Let
= <u><em>sample proportion of satisfied customers</em></u>
The z-score probability distribution for the sample proportion is given by;
Z =
~ N(0,1)
where, p = population proportion of satisfied customers = 90%
n = sample of customers = 80
Now, the probability of getting a sample with 80% satisfied customers or less is given by = P(
80%)
P(
80%) = P(
) = P(Z
-2.24) = 1 - P(Z < 2.24)
= 1 - 0.9875 = <u>0.0125</u>
The above probability is calculated by looking at the value of x = 2.24 in the z table which has an area of 0.9875.
Answer:
The worst case run time of Find2D is O(n²) because the worst case run time of arrayFind is O(n) and this function will be called for n rows from Find2D algorithm, hence O(n²)
.
An algorithm is said to have linear time if its worst case run time is O(n). Since it is O(n²) for Find2D, it is not a linear time algorithm
Step-by-step explanation:
Answer:
58 degrees
Step-by-step explanation:
90 - 32 = 58
Answer:
The number of large size candles sells are 12 and the number of small size candles are 5 .
Step-by-step explanation:
As given
Sia sells large candles for $3 each and small candles for $2 each.
She sold 17 candles for $46.00.
Let us assume that the large size candle sells are x .
Let us assume that the small size candle sells are y.
Equation becomes
x + y = 17
3x + 2y = 46
Multiply x + y = 17 by 3 and subtracted from 3x + 2y = 46 .
3x - 3x + 2y - 3y = 46 - 51
-y = - 5
y = 5
Put in the equation x + y = 17 .
x + 5 = 17
x = 17 - 5
x = 12
Therefore the number of large size candles sells are 12 and the number of small size candles are 5 .