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yulyashka [42]
2 years ago
9

I need help with these questions ( see image for question ).Please show working.​

Mathematics
1 answer:
antiseptic1488 [7]2 years ago
5 0

Answer:

  • k = -4 ± 2√5

Step-by-step explanation:

#22

<h3>Given </h3>
  • Equation x² -4x + 1 = k(x - 4) with equal roots
<h3>To find</h3>
  • The value of k
<h3>Solution</h3>

<u>The equation in standard form is:</u>

  • x² -4x + 1 = k(x - 4)
  • x² - 4x - kx + 1 + 4 = 0
  • x² - (k + 4)x + 5 = 0

<u>When the quadratic equation has equal roots its discriminant is zero</u>

  • D = 0
  • b² - 4ac = 0
  • (k + 4)² - 4*5 = 0
  • (k + 4)² = 20
  • k + 4 = ± √20
  • k = - 4 ± √20
  • or
  • k = -4 ± 2√5
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Answer:

Step-by-step explanation:

Hello!

The researcher wants to test if the valve plates manufactured have the expected tensile strength of 5 lbs/mm. So he took a sample of 42 valve plates and measured their tensile strength, obtaining a sample mean of X[bar]= 5.0611 lbs/mm and a sample standard deviation of S=0.2803 lbs/mm.

The study variable is:

X: tensile strength of a valve plate (lbs/mm)

The parameter of interest is the mean tensile strength of the valve plates, μ.

If the claim is that the valve plates of the sample have on average tensile strength of 5 lbs/mm, symbolically: μ = 5

a) The statistic hypotheses are:

H₀: μ = 5

H₁: μ ≠ 5

b) To determine the critical values and rejection region of a hypothesis test you need three to determine three factors of the hypothesis test:

1) The statistical hypothesis.

2) The significance level.

3) The statistic to use for the analysis.

The statistic hypothesis determines the number of critical values and the direction of the rejection region, in this case, the test is two-tailed you will have two critical values and the rejection region will be divided into two.

With the statistic, you will determine the distribution under which you will work and the significance level determines the probability of rejecting the null hypothesis.

To study the population mean you need that the variable of interest has at least a normal distribution, there is no information about the distribution of the study variable but the sample size is large enough n≥30, so you can apply the central limit theorem to approximate the distribution of the sample mean to normal: X[bar]≈N(μ;σ²/n)

Thanks to this approximation it is valid to use an approximation of the standard normal distribution for the test:

Z= \frac{X[bar]-Mu}{\frac{Sigma}{\sqrt{n} } }≈N(0;1)

The critical values are:

Z_{\alpha /2}= Z_{0.05}= -1.648

Z_{1-\alpha /2}= Z_{0.95}= 1.648

You will reject the null hypothesis if Z_{H_0}≤-1.648 or if Z_{H_0}≥1.648

You will not reject the null hypothesis if -1.648<Z_{H_0}<1.648

c)

Z_{H_0}= \frac{X[bar]-Mu}{\frac{S}{\sqrt{n} } }=  \frac{5.0611-5}{\frac{0.2803}{\sqrt{42} } }= 1.41

d) The value of the statistic is between the two critical values so the decision is to not reject the null hypothesis. Then using a significance level of 10% there is no significant evidence to reject the null hypothesis so the valve plates have on average tensile strength of 5 lbs/mm.

e) The p-value is defined as the probability corresponding to the calculated statistic if possible under the null hypothesis (i.e. the probability of obtaining a value as extreme as the value of the statistic under the null hypothesis). If the test is two-tailed, so is the p-value, you can calculate it as:

P(Z≤-1.41) + P(Z≥1.41)= P(Z≤-1.41) + (1 - P(Z≤1.41))= 0.079 + ( 1 - 0.921)= 0.158

p-value: 0.158

I hope it helps!

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3 years ago
Is the discriminant positive negative or zero?
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Answer:

Sorry the picture is blocked on my chromebook but i hope this helps

Step-by-step explanation:

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A consumer group is testing camp stoves. To test the heating capacity of a stove, they measure the time required to bring 2 quar
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Answer:

a

The decision rule  is  

Reject the null hypothesis

  The conclusion is  

There is sufficient evidence to show that there is a difference between the performances of these two models

b

The  95% confidence interval is  0.224   <  \mu_1 - \mu_2  < 2.776

Step-by-step explanation:

From the question we are told that

    The sample size is  n  =  36

    The first sample mean is  \= x_1   =  11.4

    The first standard deviation is  s_1 =  2.5

    The second sample mean is   \= x_2 =  9.9

     The second standard deviation is  s_2 =  3.0

      The level of significance is  \alpha  =  0.05

The null hypothesis is  H_o  :  \mu_1 - \mu_2 = 0

The alternative hypothesis is H_a :  \mu_1 - \mu_2 \ne 0

Generally the test statistics is mathematically represented as

      z =  \frac{ (\= x_1 - \= x_2 ) - (\mu_1 - \mu_2 ) }{ \sqrt{ \frac{s_1^2 }{n} + \frac{s_2^2 }{ n}  } }

=>    z =  \frac{ ( 11.4  - 9.9) - 0  }{ \sqrt{ \frac{2.5^2 }{36} + \frac{ 3^2 }{36 }  } }

=>     z = 2.3

From the z table  the area under the normal curve to the left corresponding to  2.3 is  

       P( Z >  2.3 ) =  0.010724

Generally the p-value is mathematically represented as

      p-value =  2 * P( Z >  2.3 )

=>    p-value  =  2 * 0.010724

=>    p-value  =  0.02

From the value obtained we see that  p-value  <  \alpha hence  

The decision rule  is  

Reject the null hypothesis

  The conclusion is  

There is sufficient evidence to show that there is a difference between the performances of these two models

Considering question b

From the question we are told the confidence level is  95% , hence the level of significance is    

      \alpha = (100 - 95 ) \%

=>   \alpha = 0.05

Generally from the normal distribution table the critical value  of  \frac{\alpha }{2} is  

   Z_{\frac{\alpha }{2} } =  1.96

Generally the margin of error is mathematically represented as  

      E = Z_{\frac{\alpha }{2} } *  \sqrt{ \frac{s_1^2 }{n } + \frac{s_2^2}{n}}

 => E = 1.96  *    \sqrt{ \frac{2.5^2 }{ 36 } + \frac{ 3^2}{36}}

  => E = 1.276

Generally 95% confidence interval is mathematically represented as  

      ( \= x_1 - \= x_2) -E <  \mu_1 - \mu_2  < ( \= x_1 - \= x_2) + E

=>  ( 11.4 - 9.9 ) -1.276  <  \mu_1 - \mu_2 < ( 11.4 - 9.9 ) + 1.276

=>  0.224   <  \mu_1 - \mu_2  < 2.776

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