Express 0,45 as a common fraction in simplest form

2 answers:

8 0

In order to express 0.45 as a common fraction, all you have to do is first divide 45 to 100. So in order to get the answer to this, you just have to put 45 as the numerator and 100 as the denominator. This will become 45/100. To turn it into its simple form, you have to first ask yourself what is a common divisible number for the two. 5 can be divided by 45 and 100 so 5 can be used. So the final answer, if you make it into simplest form, will be 9/20

Anna71 [15]3 years ago

7 0

If you would like to know what is 0.45 as a common fraction in its simplest form, you can calculate this using the following steps:

0.45 = 45/100

45/100 simplifies to 9/20 (the common factor of 45 and 100 is 5, so you can divide both numbers by 5).

The correct result would be 9/20.

You might be interested in

Plz help will give brainliest and points

PilotLPTM [1.2K]

The answer is C wnmdkdkdkdkdkdkdkdkdkdkd

6 0

3 years ago

If 5 out of 25 people like chocolate ice cream, what percent of the people do not like chocolate ice cream

d1i1m1o1n [39]

100 - ((5÷25)x100),
hence C. 80%

7 0

3 years ago

Read 2 more answers

The mean rent of a 3-bedroom apartment in Orlando is $1300. You randomly select 10 apartments around town. The rents are normall

lana [24]

Answer:

96.49% probability that the mean rent is more than $1100

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