All categories

2 years ago

Kim buys a coffee for 0.85 and a roll for 1.70 he give 5 dollares how much does he get back

Mathematics

2 answers:

podryga [215]2 years ago

8 0

Answer:

first you will need to add up the two items that Kim is purchasing. 0.85+1.70.

0.85+1.70=2.55

Once you have the total of the costs you will subtract it by the amount of money Kim has. 5.00.

5.00-2.55=2.45.

Kim will get back 2.45 if he pays with 5 dollars.

Hope this helps! :D

Sladkaya [172]2 years ago

4 0

Answer:

$2.45

Step-by-step explanation:

Kim bought two items so you want to add their total together

1.70+0.85=2.55

if she paid with a 5 and needs change you do

5-2.55=2.45

You might be interested in

Tyler took out a loan at a 14.7% APR, compounded monthly, to buy a boat,

Zanzabum

Answer:

14.4%, compounded monthly

Step-by-step explanation:

APEX

7 0

3 years ago

Read 2 more answers

According to a Yale program on climate change communication survey, 71% of Americans think global warming is happening.† (a) For

SpyIntel [72]

Answer:

a) 0.2741 = 27.41% probability that at least 13 believe global warming is occurring

b) 0.7611 = 76.11% probability that at least 110 believe global warming is occurring

Step-by-step explanation:

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$

In which $C_{n,x}$ is the number of different combinations of x objects from a set of n elements, given by the following formula.

$C_{n,x} = \frac{n!}{x!(n-x)!}$

And p is the probability of X happening.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

Normal probability distribution

Problems of normally distributed samples 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.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .