Teddy is rolling a die and writing the number that shows. The collection of the data is with replacement. (True or False)

Write an equation for the line that passes through the points (-4,8) and (-4,-3)

erma4kov [3.2K]

Answer:

(-3-8)/(-4+4)= -11/0= no slope and undefined

Step-by-step explanation:

8 0

3 years ago

Read the following two statements. Then, if possible, use the Law of Detachment to draw a conclusion.

jeyben [28]

<span>The hypothesis is : If Robbie wants to save money to buy a car. Conclusion : he must get a part-time job.

Robbie already started the new job yesteday. So, that makes the hypothesis true.

So, the conclusion would be : Robbie will save money to buy a car/ Robbie will buy a car.</span>

8 0

3 years ago

Read 2 more answers

Explain how to find the estimated sum of 5/8+2/9 . Make sure to include at least one type of model.

OverLord2011 [107]

In this expression you would have to use the PEMDAS method. First divide, so (5 divided by 8) + (2 divided by 9).
The answer you would get is: (0.625) + (0.222)
The final answer is: 0.847

8 0

3 years ago

72 grams equals how many miligrams

Liula [17]

72000...............

8 0

3 years ago

Read 2 more answers

Life Expectancies In a study of the life expectancy of people in a certain geographic region, the mean age at death was years an

Sphinxa [80]

Answer:

The probability that the mean life expectancy of the sample is less than X years is the p-value of $Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}$ , in which $\mu$ is the mean life expectancy, $\sigma$ is the standard deviation and n is the size of the sample.

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.

We have:

Mean $\mu$ , standard deviation $\sigma$ .

Sample of size n:

This means that the z-score is now, by the Central Limit Theorem:

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

Find the probability that the mean life expectancy will be less than years.

The probability that the mean life expectancy of the sample is less than X years is the p-value of $Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}$ , in which $\mu$ is the mean life expectancy, $\sigma$ is the standard deviation and n is the size of the sample.

8 0

2 years ago