1. What is the median of the data represented in the line plot below?<br> 0<br> 1<br> 2<br> 3

Divide £42 in a ratio of 4:6

NISA [10]

4:6
4+6 =10

£42 / 10 = £4.20

£4.20 * 4 = £16.80
£4.20 * 6 = £25.20

Please make this answer the brainiest!

3 0

3 years ago

What is 8.4/4 - 4.9+1.6/25

WINSTONCH [101]

Answer:

-2.736

Step-by-step explanation:

FOLLOW PEMDAS

8.4/4= 2.1

1.6/25= .64

2.1-4.9= -2.8

-2.8+.064=

-2.736

7 0

3 years ago

The mean cost of a five pound bag of shrimp is 50 dollars with a variance of 64. If a sample of 43 bags of shrimp is randomly se

anyanavicka [17]

Answer:

0.4122 = 41.22% probability that the sample mean would differ from the true mean by greater than 1 dollar

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(which is the square root of the variance) $\sigma$ , 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 random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sample means with size n of at least 30 can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$