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Romashka [77]
3 years ago
13

1st term in expansion of (x - y)

Mathematics
1 answer:
Andreas93 [3]3 years ago
7 0

Step-by-step explanation:

x y is the the side of the perimeter if u know what I mean

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Can anyone help me on any of the questions?​
ehidna [41]

Answer:

7.) about 3 inches per hour

Step-by-step explanation:

7 0
3 years ago
Answer these please tell me <br> 1. What the error was<br> 2. How can U check ur answer
emmainna [20.7K]

Answer:

The first one: the error was that the 3 shouldn’t have been moved but the 5 should have. The correct answer is k=-8

The second one: the error was that they added the 6 and 4, you would only get -10 if the 4 was - the correct answer is -2

You can check your answer by plugging in your answer to the variable and making sure both side equal each other

Step-by-step explanation:

The first one: the 5 should be - from both side so you get k=-8

The second one: the 4 should be + to both sides. And the -6 and +4 should be added together to get n=-2

Remember you always want to get the variables by themselves.

Sorry that was a lot. Hope it helps!

8 0
3 years ago
What is 0.969696 repeating as a fraction?
Black_prince [1.1K]

Answer:

\frac{32}{33}

5 0
2 years ago
I will give brainiest to whoever answers correctly !!
Lena [83]
Answer: the mark up price of the fish dinner is around 36.36%

Explanation: 18.75 - 13.75/13.75=5
5 divided by 13.75= 0.36363636.

Hope this helps!
3 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
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