PLEASE HELP ME FAST!!!

Mathematics

1 answer:

SVETLANKA909090 [29]3 years ago

3 0

Answer:

16,7

Step-by-step explanation:

You might be interested in

A fish tank holds 95 gallons of water but is losing 4 gallons per day. A second fish tank contains 40 gallons but has 5 gallons

Bingel [31]

After Day 7 the Second would have more water.

8 0

3 years ago

Here is the assignment : You are "selling" the polynomial. You must convince the buyer you have the Best polynomial on the marke

belka [17]

<h2>explanation: give me brainiest</h2>

Step-by-step explanation:

x^3-10x^2+28x-24=0

4 0

3 years ago

Harry Hess proposed that when two oceanic plates met each other, the denser plate would sink under the less dense plate. This is

svet-max [94.6K]

This is known as a subduction zone.

6 0

3 years ago

Is y=1/2x^2+5x-10 up or down

poizon [28]

Answer:

it is up

Step-by-step explanation:

5 0

3 years ago

Fill in the blank. In a drive thru performance study, the average service time for McDonald's is 203.21 seconds with a standard

Alenkasestr [34]

Answer:

5) 203.35

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