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3 years ago

6^3+5(8+0.2)= can someone tell me the steps i know its 257 i need the steps

Mathematics

1 answer:

Sav [38]3 years ago

3 0

Step 1 distribute the 5 across (8+0.2)

6^3+5(8+0.2)

6^3+40+1

6^3+41 (I simplified the +40 and the +1)

Step 2 take 6 to the power of 3

6^3+41

6x6x6 6x6=36 36x6=216

216+41 (Simplify!)

257

I hope this helped!

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If the measure of base angle ABC is 75°, what is m∠BAC?

Rudik [331]

B
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3 0

3 years ago

Read 2 more answers

A rectangular storage container with an open top is to have a volume of 10 m3. The length of this base is twice the width. Mater

Gala2k [10]

L = 2 W
B = L x W = 2 W²
Side Area = 2 W H + 2 L H = 2 H ( W + L ) = 6 H W
V = 2 W² H = 10
H = 5 / W²
Cost = 15 * 2 W² + 9 * 5/W
= 30 W² + 270/ W
C ` = 60 W - 270 / W²
= ( 60 W² - 270 ) / W² = 0
60 W² = 270
W ² = 270 : 60
W² = 4.5
W = √ 4.5 = 2.12
Cost (min) = 15 * 2 * 4.5 + 30 / 2.12 = 135 + 14.15 = $149.15
Answer: The cost of materials for the cheapest such container is $149.15.

8 0

3 years ago

You are studying the relationship between the history of early childhood trauma (categorized as trauma/no trauma) and weight in

jeka57 [31]

Answer:

You can decide to reject the Null Hypothesis at p < 0.05.

Step-by-step explanation:

In this case, the relationship between the history of early childhood trauma and weight in adulthood are being studied.

The categories of childhood trauma are:

Trauma and No trauma.

So, number of rows is, r = 2.

The categories of weight in adulthood are:

Low to normal, Overweight, and Obese

So, number of columns is, c = 3.

The distribution of the statistic $\chi^{2}$ is chi-square with (r - 1)(c - 1) degrees of freedom, where r represents the number of rows in the two-way table and c represents the number of columns.

Compute the degrees of freedom as follows:

$df = (r-1)(c-1)=(2-1) \times (3-1) = 2$

It is provided that the calculated value of Chi-square test statistic is 18.26.

Compute the p-value of the test as follows:

$p-value=P(\chi^{2}_{2}\geq 18.26)\\=0.000108\\\approx0.00011$

Decision rule:

The null hypothesis will be rejected if the p-value of the test is less than the significance level.

The significance level is, α = 0.05.

p-value = 0.00011 < α = 0.05.

The null hypothesis will be rejected at 5% level of significance.

Thus, the complete statement is:

"You can decide to reject the Null Hypothesis at p < 0.05."

4 0

3 years ago

Please answer ASAP! The Fergusons decided to book the room at the price that Mrs. Ferguson was given, $2075, because it included

Alex787 [66]

So what you should do is
15% off, then add tax or
2075 times 0.85 times 1.185=2090.04 about

you can't just add and subtract percents because they are percents of different things

what he did was
he found 15% of 2075 and 18.5% of 2075 then found the difference and added to 2075 to find his total

what he should have done is
found the discounted price (15% off) then found the tax on that

first way
2075 times 0.15=311.25
2075-311.25=1763.75
1763.75 times 0.185=326.29375
1763.75-326.29375=2090.04

2nd way (easy, if you understand commutative property and stuff)
100-15=85
1+0.185=1.185
2075*0.85*1.185=2090.04

answer should be $2090.04

7 0

3 years ago

In a given year, the average annual salary of a NFL football player was $189,000 with a standard deviation of $20,500. If a samp

nika2105 [10]

Answer:

15.15% probability that the sample mean will be $192,000 or more.

Step-by-step explanation:

To solve this problem, 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 random variable X, with mean $\mu$ and standard deviation $\sigma$ , a large sample size can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$