How to convert between the diameter and radius of a circle?.

A density graph is used to find the probability of a discrete random variable

IRINA_888 [86]

Answer:

False

Step-by-step explanation:

This is false because A density graph is not used to find the probability of a discrete random variable taking on a range of values. This is because you have to use a calculations instead of a graph. The correct how to calculate is: Determine a single event with a single outcome. Identify the total number of outcomes that can occur. Divide the number of events by the number of possible outcomes.

Therefore, it's B ( false).

4 0

3 years ago

A spinner has four sections lettered A, B, C, and D. The table shows the results of several spins. Find the experimental probabi

Degger [83]

Experimental probability is the outcome during a certain experiment. add up the total number of times it was spinned. You should get 40. To find the experimental probability of each section, simply divide the number by 40. This will give you the percentage for each one. For example, spinner A. 14/40=.35 Multiply this by one hundred to find the percentage (35%). Do this for all and let me know if you need help converting them to fractions. :)

5 0

3 years ago

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4- A manufacturing process produces items whose weights are normally distributed. It is known that 22.57% of all the items produ

galben [10]

Answer:

$\\ \mu = 118\;grams\;and\;\sigma=30\;grams$

Step-by-step explanation:

We need to use z-scores and a standard normal table to find the values that corresponds to the probabilities given, and then to solve a system of equations to find $\\ \mu\;and\;\sigma$ .

<h3>First Case: items from 100 grams to the mean</h3>

For finding probabilities that corresponds to z-scores, we are going to use here a <u>Standard Normal Table </u><u><em>for cumulative probabilities from the mean </em></u><em>(Standard normal table. Cumulative from the mean (0 to Z), 2020, in Wikipedia) </em>that is, the "probability that a statistic is between 0 (the mean) and Z".

A value of a z-score for the probability P(100<x<mean) = 22.57% = 0.2257 corresponds to a value of z-score = 0.6, that is, the value is 0.6 standard deviations from the mean. Since this value is <em>below the mean</em> ("the items produced weigh between 100 grams up to the mean"), then the z-score is negative.

Then

$\\ z = -0.6\;and\;z = \frac{x-\mu}{\sigma}$

$\\ -0.6 = \frac{100-\mu}{\sigma}$ (1)

<h3>Second Case: items from the mean up to 190 grams</h3>

We can apply the same procedure as before. A value of a z-score for the probability P(mean<x<190) = 49.18% = 0.4918 corresponds to a value of z-score = 2.4, which is positive since it is after the mean.

Then

$\\ z =2.4\;and\; z = \frac{x-\mu}{\sigma}$