I need help!!<br> I don’t get it!!

A commercial jet has been instructed to climb from its present altitude of 6000 feet to a cruising altitude of 30,000 feet. If t

Lunna [17]

An easier way of doing this would be to subtract the initial attitude from the final attitude and divide by the rate of increase
= 30000 - 6000÷4000
= 24000÷4000
=6mins

8 0

2 years ago

Translate 1 hundreds 4 ones 2 tens and 1 tenths

Kisachek [45]

The translated answer would be 124.1

8 0

2 years ago

A 4" by 6" by 8" rectangular solid is cut by slicing through the midpoint of three adjacent edges. What is the number of inches

Triss [41]

Answer:

22.078

Step-by-step explanation:

I have attached the images above

7 0

2 years ago

Suppose a research firm conducted a survey to determine the mean amount steady smokers spend on cigarettes during a week. A samp

shutvik [7]

Answer:

0.9910 = 99.10% probability that a sample of 170 steady smokers spend between $19 and $21

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 estabilishes 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 $s = \frac{\sigma}{\sqrt{n}}$ .