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3 years ago

Solve for x. -3x = -15 x = -5 x = 5 x = -45

Mathematics

2 answers:

Aleks [24]3 years ago

7 0

-3x = -15 divide both sides by (-3)

-3x:(-3)=-15:(-3)

x = 5

Gnom [1K]3 years ago

5 0

Answer:

The answer is b, 5

Step-by-step explanation:

-3x = -15

(it sometimes helps to flip it, so that's what I'm going to do here to help it to make more sense)

x(-3) = -15

x(-3) devided by (-3) = -15 devided by (-3)

when you devide a negitive by a negative the answer will be positive

the absolute value of 15 devided by three is 5

your answer is a positive five, or just 5

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The Brooklyn District Attorney's office analyzed the leading (leftmost) digits of check amounts in order to identify fraud. The

iragen [17]

Answer:

The expected number of checks among 784 that should have a leading digit of "1" is 236.

Step-by-step explanation:

Let X = number of checks that has the leading digit as "1".

The probability of a check having a leading digit as "1" is, p = 0.301.

The number of checks issued by a suspected company is, n = 784.

A check is having a leading digit "1" is independent of other checks.

A randomly selected check either has the leading digit 1 or not.

The success of the experiment is defined as, a check having the digit "1" as the leading digit.

The random variable X follows a Binomial distribution with parameters n = 784 and p = 0.301.

The expected value of a random variable is the average number of times the random variable occurs.

The formula to compute the expected value of a Binomial distribution is:

$E(X)=n\times p$

Compute the expected value of X as follows:

$E(X)=n\times p\\$

$=784\times 0.301\\=235.984\\\approx236$

Thus, the expected number of checks among 784 that should have a leading digit of "1" is 236.

7 0

4 years ago

25+18 divided by 6-1

forsale [732]

40R3 it 40r3the answer is

8 0

3 years ago

Read 2 more answers

Can someone help me out

Svetradugi [14.3K]

The answer is g4 -2 hope this helps

6 0

4 years ago

Read 2 more answers

Re-posting because I need help.. Please help and show how you got the answer..

Nesterboy [21]

Answer:

Explicit: -2*2^(n-1)

Recursive: 2*aₙ₋₁

Step-by-step explanation:

To write a explicit formula for this geometric sequence you follow the following formula/template

Firstnumber*commonratio^(n-1)

Seeing that the common ratio is 2 we can start plugging numbers in and get

-2*2^(n-1)

For a recursive formula we follow the following template

common ratio * the n-1 term

So we could write this as

2*aₙ₋₁

8 0

3 years ago

When dealing with the number of occurrences of an event over a specified interval of time or space, the appropriate probability

sdas [7]

Answer:

a) Poisson distribution

use a Poisson distribution model when events happen at a constant rate over time or space.

Step-by-step explanation:

Poisson distribution

Counts based on events in disjoint intervals of time or space produce a Poisson random variable.

A Poisson random variable has one parameter, its mean λ

The Poisson model uses a Poisson random variable to describe counts in data.

use a Poisson distribution model when events happen at a constant rate over time or space.

Hyper geometric probability distribution:-

The Hyper geometric probability distribution is a discrete probability distribution that describes the probability of successes (random draws for which the object drawn has a specified feature) in draws without replacement, from a finite population of size that contains exactly objects with that feature where in each draw is either a success or failure.

This is more than geometric function so it is called the Hyper geometric probability distribution 

Binomial distribution

The number of successes in 'n' Bernoulli trials produces a Binomial distribution . The parameters are size 'n' success 'p' and failure 'q'
The binomial model uses a binomial random variable to describe counts of success observed for a real phenomenon.

Finally use a Binomial distribution when you recognize distinct Bernoulli trials.

Normal distribution:-

normal distribution is a continuous distribution in which the variate can take all values within a range.

Examples of continuous distribution are the heights of persons ,the speed of a vehicle., and so on

Associate normal models with bell shaped distribution of data and the empirical rule.

connect Normal distribution to sums of like sized effects with central limit theorem

use histograms and normal quantile plots to judge whether the data match the assumptions of a normal model.

Conclusion:-

Given data use a Poisson distribution model when events happen at a constant rate over time or space.

3 0

4 years ago