A rectangle has a perimeter ofb12 yards and a height of 2 yards what is the length of the base

The baseball coach is 70 inches tall. How tall is the child?

tankabanditka [31]

The child is <u>59.4 inches tall</u>, assuming the length from the coach's shoulder to his head cap is approximately 10 inches.

<h3>What is Heigth?</h3>

Height refers to the vertical distance between the top and bottom of something.

Height measures the length of some objects or persons vertically to determine whether it is high or low, according to some ascertained criteria.

<h3>Data and Calculations:</h3>

Baseball coach's height = 70 inches

Coach's shoulder to head = 10.6 inches

Height of the child standing slightly below the coach's shoulder = 59.4 inches (70 - 10.6)

Thus, the child standing slightly below the coach's shoulder is 59.4 inches tall.

Learn more about height measurements at brainly.com/question/73194

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<h3>Question Completion:</h3>

Assume that the height of the coach from his shoulder to the head is 10.6 inches.

6 0

2 years ago

In a completely randomized experimental design, three brands of paper towels were tested for their ability to absorb water. Equa

arlik [135]

Answer:

Yes. At this significance level, there is evidence to support the claim that there is a difference in the ability of the brands to absorb water.

Step-by-step explanation:

<em>The question is incomplete:</em>

<em>The significance level is 0.05.</em>

<em>Brand X: 91, 100, 88, 89</em>

<em>Brand Y: 99, 96, 94, 99</em>

<em>Brand Z: 83, 88, 89, 76</em>

We have to check if there is a significant difference between the absorbency rating of each brand.

Null hypothesis: all means are equal

$H_0:\mu_x=\mu_y=\mu_z$

Alternative hypothesis: the means are not equal

$H_a: \mu_x\neq\mu_y\neq\mu_z$

We have to apply a one-way ANOVA

We start by calculating the standard deviation for each brand:

$s_x^2=30,\,\,s_y^2=6,\,\,s_z^2=35.33$

Then, we calculate the mean standard error (MSE):

$MSE=(\sum s_i^2)/a=(30+6+35.33)/3=71.33/3=23.78$

Now, we calculate the mean square between (MSB), but we previously have to know the sample means and the mean of the sample means:

$M_x=92,\,\,M_y=97,\,\,M_z=84\\\\M=(92+97+84)/3=91$

The MSB is then:

$s^2=\dfrac{\sum(M_i-M)^2}{N-1}\\\\\\s^2=\dfrac{(92-91)^2+(97-91)^2+(84-91)^2}{3-1}\\\\\\s^2=\dfrac{1+36+49}{2}=\dfrac{86}{2}=43\\\\\\\\MSB=ns^2=4*43=172$