Part A.
7.8 is a rational number between 7.7 and 7.9.
It is rational because it can be written as a fraction of integers, such as 78/10.
Part B.
sqrt(60) = 7.75
sqrt(60) cannot be written as a fraction of integers. It is a decimal number that never ends and never repeats.
Answer:
The equation for the total number of strings ordered is
X+Y=80
The equation based on the price of each type of string and the total value of the order is
4.50 x +1.50 y = 225
Step-by-step explanation:
With the choices you gave, the answer to this question is the first statement, "2 loaves of bread and 4 batches of muffins''. I arrived with the answer through multiplying the amount of flour and sugar required for each loaf of bread and batch of muffins.
This is the following condition in order to get the specific output for this specific problem: if is_a_prime(n):<span> is_prime = True</span> <span><span>Now all you have to do is write is_a_prime().
For the hard code for this problem:
</span>if n == 2:<span>
is_prime = True
elif n % 2 == 0:
is_prime = False
else:
is_prime = True
for m in range (3, int (n * 0.5) + 1, 2):
if n % m == 0:
is_prime = False
<span>break.</span></span></span>
<span>
To add, a high-level programming language that is widely used for general-purpose programming<span>, created by Guido van Rossum and first released in 1991 is called Python.</span></span>
Answer:
The value of the test statistic is t=1.12.
Step-by-step explanation:
This is a hypothesis test for the difference between populations means.
The claim is that the mean amount of time required to reach a customer service representative significantly differs between the two hotels.
Then, the null and alternative hypothesis are:
The sample 1, of size n1=20 has a mean of 2.65 and a standard deviation of √2.952=1.72.
The sample 2, of size n2=20 has a mean of 2.01 and a standard deviation of √2.952=1.89.
The difference between sample means is Md=0.64.
The estimated standard error of the difference between means is computed using the formula:
Then, we can calculate the t-statistic as:
