explain why multiplying the numerator and denominator of a fraction by the same number results in an equivalent fraction.

Arrange the following in descending order - 5, 0, -15, 2.5, 2.05

ExtremeBDS [4]

Answer:

2.5, 2.05, 0, -5, -15

Step-by-step explanation:

for negative numbers the bigger is worth less

4 0

3 years ago

Subtract 24ab-10b-18a from 30ab+12b+4a

RUDIKE [14]

Answer:

-6ab-22a-22b

Step-by-step explanation:

4 0

3 years ago

shawn is baking cookies. the receipt asks for 2 1/4 cups of flour and 1/4 cup of cocoa shawn wants to increase the recipe by 50%

salantis [7]

2.25/2= 1.125

2.25+1.125= 3.375

.25/2=.125

0.375

3 and 3/8 cups of flour, and 3/8 cups of cocoa.

I hope this helps!
~kaikers

5 0

4 years ago

Assume that females have pulse rates that are normally distributed with a mean of mu equals 72.0 beats per minute and a standard

larisa86 [58]

Answer:

a) 36.88% probability that her pulse rate is between 66 beats per minute and 78 beats per minute

b) 66.30% probability that they have pulse rates with a mean between 66 beats per minute and 78 beats per minute

c)

C.

Since the original population has a normal distribution, the distribution of sample means is a normal distribution for any sample size.

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 sample means with size n of at least 30 can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$

In this problem, we have that:

$\mu = 72, \sigma = 6.5$

a. If 1 adult female is randomly selected, find the probability that her pulse rate is between 66 beats per minute and 78 beats per minute.

The probability is?

This is the pvalue of Z when X = 78 subtracted by the pvalue of Z when X = 66. So

X = 78

$Z = \frac{X - \mu}{\sigma}$

$Z = \frac{78 - 72}{12.5}$

$Z = 0.48$

$Z = 0.48$ has a pvalue of 0.6844

X = 66

$Z = \frac{X - \mu}{\sigma}$

$Z = \frac{66 - 72}{12.5}$

$Z = -0.48$

$Z = -0.48$ has a pvalue of 0.3156

0.6844 - 0.3156 = 0.3688

36.88% probability that her pulse rate is between 66 beats per minute and 78 beats per minute

b. If 4 adult females are randomly selected, find the probability that they have pulse rates with a mean between 66 beats per minute and 78 beats per minute

The probability is?

Now we have $n = 4, s = \frac{12.5}{\sqrt{4}} = 6.25$