a musician 's hair was originally 3 inches long. She asked her hairdresser to cut 5/6 off. how many inches did she cut?

Pretty sure it’s the second option because length would be 3w+2
and width would be w+1 and with area you have to multiply so it would just be the (w+1)(3w+2)

5 0

3 years ago

Read 2 more answers

Jeff was already 7 miles out of town when his sister

Nikolay [14]

The sister catches up Jeff after 2 hours

Step-by-step explanation:

We can write Jeff's position and his sister position at time t using the following expressions:

- Jeff position:

$x_j(t) = 7 + 2.5 t$

where:

7 is the initial position of Jeff when his sister sarts chasing him

2.5 is Jeff's velocity (in miles/hour), so its position increases by 2.5 miles for each hour

t is the time measured in hours

- Sister position:

$x_s(t) = 6t$

where

6 is the sister velocity (her position increases by 6 miles for every hour)

t is the time measured in hours

The sister catches up Jeff when the two positions are equal, so

$x_j(t) = x_s(t)\\7+2.5t=6t$

And solving for t,

$7+2.5t-2.5t=6t-2.5t\\7=3.5t\\t=\frac{7}{3.5}=2 h$

So, the sister catches Jeff after 2 hours.

Learn more about speed:

brainly.com/question/8893949

#LearnwithBrainly

5 0

3 years ago

Suppose the weights of Farmer Carl's potatoes are normally distributed with a mean of 8.0 ounces and a standard deviation of 1.1

svet-max [94.6K]

Answer:

a) 0.9959 = 99.59% probability that the mean weight is less than 9.3 ounces

b) 0.0129 = 1.29% probability that the mean weight is more than 9.0 ounces

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