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3 years ago

94.4=8(m+3.2) what is m

Mathematics

2 answers:

Lunna [17]3 years ago

8 0

M=8.6 have a good day

NemiM [27]3 years ago

8 0

Hello!

The correct answer is m = 8.6 how do we find this out?

Here's the equation.

94.4 = 8 * (8.6 + 3.2)

Simplify from here.

94.4 = 8 * (8.6 + 3.2) ---> 94.4 = 8 * 11.8

94.4 = 8 * 11.8 ---> 94.4 = 94.4

Hope this helps! ☺♥

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An astronaut who weighs 85 kilograms on earth weighs 14.2 kilograms on the moon. How much would a person weigh on the moon if th

STatiana [176]

Answer:

Weight on the moon=x=15.87 kilograms

Step-by-step explanation:

This can be expressed as;

Weight on earth=Constant×Weight on moon

where;

Weight on moon=14.2 kilograms

Constant=k

Weight on Earth=85 kilograms

Replacing in the expression above;

85=14.2×k

k=(85/14.2)=5.986

If the person weighs 95 kilograms on Earth;

Weight on the earth=Constant×Weight on moon

where;

Weight on the moon=x

Constant=5.986

Weight on the earth=95 kilograms

Replacing;

95=5.986×x

x=95/5.986=15.87

Weight on the moon=x=15.87 kilograms

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3 years ago

Tom opens a bank account and makes an initial deposit of $500. The banker tells Tom that he is going to receive

Katena32 [7]

Bank balance after 15 years is $950

Step-by-step explanation:

Step 1: Find the simple interest on the principal amount using the formula SI = PRT/100 where Principal (P) = $500, Rate of Interest (R) = 6% and Time(T) = 15 years

⇒ SI = 500 × 6 × 15/100 = $450

Step 2: Find total amount using the formula Amount = P + SI

⇒ Amount = 500 + 450 = $950

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3 years ago

What is the difference between discrete vs continuous data

Sergeeva-Olga [200]

With continuous data, it is possible to find the midpoint of any two distinct values. For instance, if h = height of tree, then its possible to find the middle height of h = 10 and h = 7 (which in this case is h = 8.5)

On the other hand, discrete data can't be treated the same way (eg: if n = number of people, then there is no midpoint between n = 3 and n = 4).

-------------------------------------

With that in mind, we have the following answers

1) Continuous data. Time values are always continuous. Any two distinct time values can be averaged to find the midpoint

2) Continuous data. Like time values, temperatures can be averaged as well.

3) Discrete data. Place locations in a race or competition are finite and we can't have midpoints. We can't have a midpoint between 9th and 10th place for instance.

4) Continuous data. We can find the midpoint and it makes sense to do so when it comes to speeds.

5) Discrete data. This is a finite number and countable. We cannot have 20.5 freshman for instance.

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3 years ago

Help please :) (asap)

ryzh [129]

x^2 - x - 6= 0

(x - 3) ( x + 2) = 0

Equating

x - 3 = 0

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4 0

3 years ago

Read 2 more answers

A report indicated that 37% of adults had received a bogus email intended to steal personal information. Suppose a random sample

fiasKO [112]

Answer:

5.05% probability that no more than 34% had received such an email.

Step-by-step explanation:

We use the binomial approximation to the normal to solve this problem.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

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 $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .