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3 years ago

Find the constant $a$ such that\[(x^2 - 3x + 4)(2x^2 +ax + 7) = 2x^4 -11x^3 +30x^2 -41x +28.\]

Mathematics

1 answer:

Colt1911 [192]3 years ago

4 0

The value of constant a is -5

Further explanation:

We will use the comparison of co-efficient method for finding the value of a

So,

Given

$(x^2 - 3x + 4)(2x^2 +ax + 7)\\= x^2((2x^2 +ax + 7)-3x((2x^2 +ax + 7)+4(2x^2 +ax + 7)\\= 2x^4+ax^3+7x^2-6x^3-3ax^2-21x+8x^2+4ax+28\\Combining\ alike\ terms\\=2x^4+ax^3-6x^3+7x^2-3ax^2+8x^2-21x+4ax+28\\= 2x^4 +(a-6)x^3+(15-3a)x^2-(21-4a)x+28\\$

As it is given that

(x^2 - 3x + 4)(2x^2 +ax + 7) = 2x^4 -11x^3 +30x^2 -41x +28

In this case, co-efficient of variables will be equal, so we can compare the coefficients of x^3, x^2 or x

Comparing coefficient of x^3

$a-6 = -11\\a = -11+6\\a = -5$

So the value of constant a is -5

Keywords: Polynomials, factorization

Learn more about factorization at:

#LearnwithBrainly

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Answer:

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Consecutive numbers. X
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3 years ago

The Salk polio vaccine experiment in 1954 focused on the effectiveness of the vaccine in combating paralytic polio. Because it w

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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

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

n₂= 200745 total children studied

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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

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

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

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

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.

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!

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