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victus00 [196]
2 years ago
11

A random variable x follows a normal distribution with mean d and standard deviation o=2. It is known that x is less than 5 abou

t 69.85% of the time. What is the mean d of this distribution?
Mathematics
1 answer:
Vaselesa [24]2 years ago
3 0

Answer:

The mean of this distribution is approximately 3.96.

Step-by-step explanation:

Here's how to solve this problem using a normal distribution table.

Let z be the

\displaystyle z = \frac{x - \mu}{\sigma}.

In this question, x = 5 and \sigma = 2. The equation becomes

\displaystyle z = \frac{5 - \mu}{2}.

To solve for \mu, the mean of this distribution, the only thing that needs to be found is the value of z. Since

The problem stated that P(X \le 5) = 69.85\% = 0.6985. Hence, P(Z \le z) = 0.6985.

The problem is that the normal distribution tables list only the value of P(0 \le Z \le z) for z \ge 0. To estimate  z from P(Z \le z) = 0.6985, it would be necessary to find the appropriate

Since P(Z \le z) = 0.6985 and is greater than P(Z \le 0) = 0.50, z > 0. As a result, P(Z \le z) can be written as the sum of P(Z < 0) and P(0 \le Z \le z). Besides, P(Z < 0) = P(Z \le 0) = 0.50. As a result:

\begin{aligned}&P(Z \le z)\\ &= P(Z < 0) + P(0 \le Z \le z) \\ &= 0.50 + P(0 \le Z \le z)\end{aligned}.

Therefore:

\begin{aligned}&P(0 \le Z \le z) \\ &= P(Z \le z) - 0.50 \\&= 0.6985 - 0.50 \\&=0.1985 \end{aligned}.

Lookup 0.1985 on a normal distribution table. The corresponding z-score is 0.52. (In other words, P(0 \le Z \le 0.52) = 0.1985.)

Given that

  • z = 0.52,
  • x =5, and
  • \sigma = 2,

Solve the equation \displaystyle z = \frac{x - \mu}{\sigma} for the mean, \mu:

\displaystyle 0.52 = \frac{5 - \mu}{2}.

\mu = 5 - 2 \times 0.52 = 3.96.

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Answer:

We conclude that a web-based company are not exceeding their goal of 90%.

Step-by-step explanation:

We are given that a web-based company has a goal of processing 90 percent of its orders on the same day they are received.

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Let p = <u><em>proportion of orders processing on the same day they are received.</em></u>

SO, Null Hypothesis, H_0 : p \leq 0.90     {means that they are not exceeding their goal of 90%}

Alternate Hypothesis, H_0 : p > 0.90      {means that they are exceeding their goal of 90%}

The test statistics that would be used here <u>One-sample z test for</u> <u>proportions</u>;

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where, \hat p = sample proportion of orders that are processed on the same day = \frac{434}{471} = 0.92

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So, <u><em>the test statistics</em></u>  =  \frac{0.92-0.90}{\sqrt{\frac{0.92(1-0.92)}{471} } }

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The value of z test statistics is 1.599.

<u>Now, at 0.025 significance level the z table gives critical value of 1.96 for right-tailed test.</u>

Since our test statistic is less than the critical value of z as 1.599 < 1.96, so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region due to which <u><em>we fail to reject our null hypothesis</em></u>.

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The general form is ...

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We note that 2π/1.2 = 5π/3. Filling in the given values, we have ...

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Option A.

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