Four friends went scuba diving. According to the following statements, who spotted sea life at the fastest rate?

1 answer:

3 0

Lance: 4/6 = 2/3 = 0.66 creatures every minute

Jasmine: 6/8 = 3/4 = 0.75 creatures every minute

Robert: 11/15 = 2.2/3 = 0.73 creatures every minute

Shilpa: 8/10 = 0.8 creatures per minute

Shilpa spotted sea life at the fastest rate (0.8 creatures every 1 minute)

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Answer:

The correct answer is:

There is a positive correlation because women's weight tend to increase when height increases (D)

Step-by-step explanation:

The units that might be used to measure each variable are:

Height : meter (m) or foot (plural, feet) (Ft.)

weight : kilograms (kg) or Pounds (lb)

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The average amount of water in randomly selected 16-ounce bottles of water is 16.15 ounces with a standard deviation of 0.45 oun

vekshin1

Answer:

0.0179 = 1.79% probability that the mean of this sample is less than 15.99 ounces of water.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use 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 $s = \frac{\sigma}{\sqrt{n}}$ .