An appropriate tip for a waiter at a restaurant is at least 15%. For a tab of $20, how much money should be left, including tip?

Calculate the second moment of area of a 4-in-diameter shaft about the x-x and yy axes, as shown.

Keith_Richards [23]

Second moment of area about an axis along any diameter in the plane of the cross section (i.e. x-x, y-y) is each equal to (1/4)pi r^4.
The second moment of area about the zz-axis (along the axis of the cylinder) is the sum of the two, namely (1/2)pi r^4.

The derivation is by integration of the following:
int int y^2 dA
over the area of the cross section, and can be found in any book on mechanics of materials.

6 0

3 years ago

I don't know what the first step is

oksano4ka [1.4K]

Add all of the ounces in the basket.
6 2/3+3 1/2+ 5

6 0

3 years ago

7) CJ was painting his apartment. In 15 minutes,

igomit [66]

y = 12x represents the gallons of paint used in x hours.

Step-by-step explanation:

CJ uses 3 gallons of paint in 15 minutes,

15 minutes = 3 gallons

1 minutes = $\frac{3}{15} = \frac{1}{5} \ gallons\\$

1 hour = 60 minutes

Gallons of paint used in 1 hour;

1 hour = $\frac{1}{5}*60=12\ gallons$

CJ uses 12 gallons of paint in 1 hour.

For x hours = 12*x = 12x

Gallons of paints used = y

y = 12x represents the gallons of paint used in x hours.

Keywords: linear equation, multiplication

Learn more about multiplication at:

#LearnwithBrainly

5 0

2 years ago

Suppose that 76% of Americans prefer Coke to Pepsi. A sample of 80 was taken. What is the probability that at least seventy perc

Anastasy [175]

Answer:

C. 0.896

Step-by-step explanation:

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

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