The distance between two cities is 600 miles. The two cities are 4 inches apart on the map. What is the scale of the map?

6. You've just received an order of silk flower arrangements from your wholesaler. You paid $20.00 each for them. Your store use

cupoosta [38]

10% of $20 is $2 (take off the end 0)
$20+10%=?
$20+$2[this is 10%]=$22
The selling price is $22

7 0

2 years ago

Plz helppp I’m dying

Lana71 [14]

Answer:

if you are dying you should call EMS

Step-by-step explanation:

7 0

2 years ago

Which best defines a pioneer species?

mixas84 [53]

The first species to populate an uninhabited

6 0

2 years ago

Majesty Video Production Inc. wants the mean length of its advertisements to be 26 seconds. Assume the distribution of ad length

Paladinen [302]

Answer:

a) By the Central Limit Theorem, approximately normally distributed, with mean 26 and standard error 0.44.

b) s = 0.44

c) 0.84% of the sample means will be greater than 27.05 seconds

d) 98.46% of the sample means will be greater than 25.05 seconds

e) 97.62% of the sample means will be greater than 25.05 but less than 27.05 seconds

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 normally distributed samples are solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore 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 pvalue, 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(also called standard error) $s = \frac{\sigma}{\sqrt{n}}$ .