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Which of the following satisfy x ≥ 4.1? Select all that apply.

natta225 [31]

Answer:

x = 4.5

x = 4.1

Step-by-step explanation:

3 0

2 years ago

Normal or natural variations in the quality of production output that are due purely to chance are _____.

nydimaria [60]

Normal or natural variations in the quality of production output that are due purely to chance are common causes.

According to the statement

we have to tell about the that cause which effect the quality and production output in the normal and natural variation.

So, For this purpose, we know that the

Common cause variation is present when the control chart of a process measure shows a random pattern of variation with all points within the control limits. When a control chart shows common cause variation, a process measure is said to be in statistical control or stable.

And due to this cause there is a lot of effect on the natural variations in the quality of production output.

So, Normal or natural variations in the quality of production output that are due purely to chance are common causes.

Learn more about common cause variation here

brainly.com/question/28040185

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6 0

2 years ago

A vending machine has 5 colors (white, red, green, blue, and yellow) of gumballs and an equal chance of dispensing each. A secon

babunello [35]

Answer:

1/20

Step-by-step explanation:

6 0

3 years ago

Find cot 0 if cos 0=3/13

natta225 [31]

3/4 root 10
you make a right triangle. use Pythagorean theorem. and find the opposite side. then reduce the radical of 160. and do tan and then flip them around to make cot.

6 0

3 years ago

Read 2 more answers

An industrial process produces batches of a chemical whose impurity levels follwo a normal distribution with standard deviation

Agata [3.3K]

Answer:

The probability is 0,0367 that the sample mean impurity level exceeds the population mean by 0.2864 grams of chemical.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Standard deviation 1.6 grams of chemical. Random sample of 100.

This means that $n = 100, s = \frac{1.6}{\sqrt{100}} = 0.16$

The probability is 0,0367 that the sample mean impurity level exceeds the population mean by how much?

Z multiplied by s, in which Z has a p-value of 1 - 0.0367 = 0.9633, so Z = 1.79.

1.79*0.16 = 0.2864.

The probability is 0,0367 that the sample mean impurity level exceeds the population mean by 0.2864 grams of chemical.

7 0

3 years ago