What is 0.75 in a fraction lowest terms?

Aaron is using a special beaker in science that is a cylinder with a radius of 2 cm and a height of 3 cm on top of a cylinder th

Vilka [71]

Since in the above case, the beaker has two sections each with different radius and height, we will divide this problem into two parts.

We will calculate the volume of both the beakers separately and then add them up together to get the volume of the beaker.

Given, π = 3.14

Beaker 1:

Radius (r₁) = 2 cm
Height (h₁) = 3 cm

Volume (V₁) = π r₁² h₁ = 3.14 x 2² x 3 = 37.68 cm³

Beaker 2:

Radius (r₂) = 6 cm
Height (h₂) = 4 cm
Volume (V₂) = π r₂² h₂ = 3.14 x 6² x 4 = 452.16 cm³

Volume of beaker = V₁ + V₂ = 37.68 + 452.16 = 489.84 cm³

7 0

2 years ago

Read 2 more answers

Claudia is making gelatin dessert for a party she plans on making 12 servings for every 5 people if each pan Claudia uses to mak

madam [21]

12×2=24
24÷8=3
she needs 3 pans

5 0

3 years ago

Would someone mind explaining this?

Nesterboy [21]

Answer:

3?

Step-by-step explanation:

i think that because it's multiplying by 3.

3*3= 9

5*3= 15

7*3= 21

9*3= 27

This is the only way i could think of helping in some sort of way! I'm sorry if it's wrong! (´。＿。｀)

Have a great day! (´。＿。｀) / (ﾉ◕ヮ◕)ﾉ*:･ﾟ✧

( ﾟдﾟ)つ Bye

8 0

3 years ago

What’s the measure of x for the for each figure?

Minchanka [31]

Answer:

a)73

b)27

c)58

d)70

6 0

3 years ago

A simple random sample of 100 observations was taken from a large population. The sample mean and the standard deviation were de

olga2289 [7]

Answer:

Se=1.2

Step-by-step explanation:

The standard error is the standard deviation of a sample population. "It measures the accuracy with which a sample represents a population".

The central limit theorem (CLT) states "that the distribution of sample means approximates a normal distribution, as the sample size becomes larger, assuming that all samples are identical in size, and regardless of the population distribution shape"

The sample mean is defined as:

$\bar X =\frac{\sum_{i=1}^n x_i}{n}$

And the distribution for the sample mean is given by:

$\bar X \sim N(\mu,\frac{\sigma}{\sqrt{n}})$

Let X denotes the random variable that measures the particular characteristic of interest. Let, X1, X2, …, Xn be the values of the random variable for the n units of the sample.

As the sample size is large,(>30) it can be assumed that the distribution is normal. The standard error of the sample mean X bar is given by:

$Se=\frac{\sigma}{\sqrt{n}}$

If we replace the values given we have:

$Se=\frac{12}{\sqrt{100}}=1.2$

So then the distribution for the sample mean $\bar X$ is:

$\bar X \sim N(\mu=80,Se=1.2)$

5 0

2 years ago