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babymother [125]
3 years ago
8

Hello please help..........

Mathematics
1 answer:
lions [1.4K]3 years ago
7 0
I got the same question sombody hell
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During the two hours of the morning rush from 8 a.m. to 10 a.m., 100 customers per hour arrive at the coffee shop. The coffee sh
Anastaziya [24]

So, 40 Customers are waiting at 10 A.M.

According to statement

Number of customers arrives at coffee shop per hour = 100

Capacity of shop for per minute per customer = 0.8 minute

Capacity of shop for customers per hour = 80

Find number of customers are by

Queue growth rate = Demand - Capacity

Put the values in the formula and find the growth rate

So,

Queue growth rate= 100 - 80 = 20.

Length of queue at 10 a.m. = 2 × 20 = 40.

So, 40 Customers are waiting at 10 A.M.

Learn more about GROWTH RATE here brainly.com/question/1437549

#SPJ4

7 0
1 year ago
Please help me please will give brainliest to anyone who is good​
hichkok12 [17]

Answer:

C

Step-by-step explanation:

N = st

Number of toothpicks = (number of students) x (toothpicks)

5 0
3 years ago
Read 2 more answers
Which is equivalent to 4x/x-7 - x+7/x
spin [16.1K]

Answer:

The answer to your question is the second choice

Step-by-step explanation:

                        4x/ (x - 7)  -  (x +7) / x

- Find the greatest common factor from x and (x - 7)

                 GCF = x(x - 7)

- Substract the terms

                     [4x(x) - (x + 7)(x - 7)] / x(x - 7)

- Simplify

                     [ 4x² - x² + 49] / x(x - 7)

                     [ 3x² + 49] / x(x - 7)

- Result

                      3x² + 49  /  x(x - 7)

                       

6 0
3 years ago
The Salk polio vaccine experiment in 1954 focused on the effectiveness of the vaccine in combating paralytic polio. Because it w
sdas [7]

Answer:

Step-by-step explanation:

Hello!

The variables of interest are:

X₁: Number of cases of polio observed in kids that received the placebo vaccine.

n₁= 201299 total children studied

x₁= 110 cases observed

X₂: Number of cases of polio observed in kids that received the experimental vaccine.

n₂= 200745 total children studied

x₂= 33 cases observed

These two variables have a binomial distribution. The parameters of interest, the ones to compare, are the population proportions: p₁ vs p₂

You have to test if the population proportions of children who contracted polio in both groups are different: p₂ ≠ p₁

a)

H₀: p₂ = p₁

H₁: p₂ ≠ p₁

α: 0.05

Z= \frac{(p'_2-p'_1)-(p_2-p_1)}{\sqrt{p'[\frac{1}{n_1} +\frac{1}{n_2} ]} }

Sample proportion placebo p'₁= x₁/n₁= 110/201299= 0.0005

Sample proportion vaccine p'₂= x₂/n₂= 33/200745= 0.0002

Pooled sample proportion p'= (x₁+x₂)/(n₁+n₂)= (110+33)/(201299+200745)= 0.0004

Z_{H_0}= \frac{(0.0002-0.0005)-0}{\sqrt{0.0004[\frac{1}{201299} +\frac{1}{200745} ]} }= -4.76

This test is two-tailed, using the critical value approach, you have to determine two critical values:

Z_{\alpha/2}= Z_{0.025}= -1.96

Z_{1-\alpha /2}= Z_{0.975}= 1.96

Then if Z_{H_0} ≤ -1.96 or if Z_{H_0} ≥ 1.96, the decision is to reject the null hypothesis.

If -1.96 < Z_{H_0} < 1.96, the decision is to not reject the null hypothesis.

⇒ Z_{H_0}= -4.76, the decision is to reject the null hypothesis.

b)

H₀: p₂ = p₁

H₁: p₂ ≠ p₁

α: 0.01

Z= \frac{(p'_2-p'_1)-(p_2-p_1)}{\sqrt{p'[\frac{1}{n_1} +\frac{1}{n_2} ]} }

The value of Z_{H_0}= -4.76 doesn't change, since we are working with the same samples.

The only thing that changes alongside with the level of significance is the rejection region:

Z_{\alpha /2}= Z_{0.005}= -2.576

Z_{1-\alpha /2}= Z_{0.995}= 2.576

Then if Z_{H_0} ≤ -2.576or if Z_{H_0} ≥ 2.576, the decision is to reject the null hypothesis.

If -2.576< Z_{H_0} < 2.576, the decision is to not reject the null hypothesis.

⇒ Z_{H_0}= -4.76, the decision is to reject the null hypothesis.

c)

Remember the level of significance (probability of committing type I error) is the probability of rejecting a true null hypothesis. This means that the smaller this value is, the fewer chances you have of discarding the true null hypothesis. But as you know, you cannot just reduce this value to zero because, the smaller α is, the bigger β (probability of committing type II error) becomes.

Rejecting the null hypothesis using different values of α means that there is a high chance that you reached a correct decision (rejecting a false null hypothesis)

I hope this helps!

8 0
3 years ago
Which data set COULD NOT be represented by the histogram shown?
igomit [66]
D. Only has 3 numbers in the 5-9 range, while the histogram shows 4. Hope this helps :)
4 0
3 years ago
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