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Marina86 [1]
3 years ago
9

An industrial engineer is planning to test the claim that the mean cycle time of a particular assembly process is less than 10 m

inutes. She sets α = 0.05 and plans to take a SRS of 100 such processes and record the cycle time for each. If the true mean cycle time of the assembly process is 9.78 minutes the power of her test is 0.85. In all possible samples of size 100 she will:
Mathematics
1 answer:
Over [174]3 years ago
3 0

Answer:

Make a Type I error 15% of the time.

Step-by-step explanation:

<em>The question is incomplete:</em>

<em>In all possible samples of size 100 she will:</em>

  1. <em>Make a Type II error 5% of the time</em>
  2. <em>Reject the null hypothesis 15% of the time</em>
  3. <em>Make a Type I error 5% of the time</em>
  4. <em>Fail to reject the null hypothesis 85% of the time</em>

Option 2 and 4 are both false because we can not estimate this probabilitites a priori.

Option 1.

The power of a test is defined as the conditional probability of rejecting the null hypothesis, given that the alternative hypothesis is true.

Then, the power of the test is complementary of the probability of failing to reject the null hypothesis, gicen that the alternative hypothesis is true. The last is the definition of the probability of a Type II error.

This means that a power of 0.85 implies a probability of (1-0.85)=0.15 of making a Type II error.

P(Type \,II\, error)=1-Power=1-0.85=0.15

The option 1 ("Make a Type II error 5% of the time") is not precise, so it is not correct.

Option 3

The significance level is 0.05. This is also the probability of making a Type I error.

The option 3 ("Make a Type I error 5% of the time") is correct.

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X=40 degrees
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7 0
2 years ago
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Saul decides to use the IQR to measure the spread of the data. Saul calculates the IQR of the data set to be 27
german

Answer:

n = 78

Step-by-step explanation:

IQR is the interquartile range of the data set.

So Saul had already arranged the data in order, that is the first step when calculating the interquartile range.

25, 30, 50, 50, 50, 50, 56, n., 250

Next, is to find the median so we could easily separate the data into quartiles.

The median of the data 25, 30, 50, 50, 50, 50, 56, n., 250 = 50

Then, arrange the data into the first quartile and the third quartile

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first quartile median = 30 + 50 = 80/2 = 40

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The interquartile range formula is the first quartile subtracted from the third quartile:

IQR = Q3 – Q1.

Since 27 is the interquartile range, n=

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3+75(2)-16(2)^2=h\\\\3+150-64=h\\\\h=89

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