Please help! It’s very confusing and it’s not 1+(n-1)1 btw

A wheelchair ramp is 16 feet Long. The ramp sits up on a 2 foot platform. How far is it from the end of the ramp to the bottom o

il63 [147K]

Answer:

√254 feet

Step-by-step explanation:

This is basically a triangle, with a height of 2, and hypotenuse of 16.

Using the Pythagorean theorem (a^2+b^2=h^2) we can find the other side.

2^2+b^2=16^2

4+b^2=256

b^2=254

b=√254

3 0

3 years ago

Please help I will give points

iVinArrow [24]

Answer:

1/32

Step-by-step explanation:

...

8 0

3 years ago

SOLVE what is J<br> 3j + 4 = 10<br> J =

tigry1 [53]

Answer: The answer is 2

Step-by-step explanation:

3j + 4 = 10 J = 2

3x2=6

6+4= 10

6 0

1 year ago

Read 2 more answers

3/2 dived by 7/8 dived by 1/2

Leviafan [203]

Answer:

3.428571429 or approximately 3.43

Step-by-step explanation:

3/2

= 1.5

7/8

= 0.875

1.5/0.875

= 1.714285714

1.714285714/0.5

= 3.428571429

or approximately 3.43

6 0

3 years ago

Gibbs Baby Food Company wishes to compare the weight gain of infants using its brand versus its competitor’s. A sample of 40 bab

Leviafan [203]

Answer:

$z=\frac{(7.6-8.1)-0}{\sqrt{\frac{2.3^2}{40}+\frac{2.9^2}{55}}}}=-0.936$

The p value can be founded with this formula:

$p_v =P(z$

Since the p value is higher than the significance level provided of 0.05 we have enough evidence to FAIL to reject the null hypothesis and we can't conclude that the true mean for the Gibbs brand is significantly lower than the true mean for the competitor

Step-by-step explanation:

Information given

$\bar X_{1}=7.6$ represent the mean for Gibbs products

$\bar X_{2}=8.1$ represent the mean for the competitor

$\sigma_{1}=2.3$ represent the population standard deviation for Gibbs

$\sigma_{2}=2.9$ represent the sample standard deviation for the competitor

$n_{1}=40$ sample size for the group Gibbs

$n_{2}=55$ sample size for the group competitor

$\alpha=0.05$ Significance level provided

z would represent the statistic

Hypothesis to verify

We want to check if babies using the Gibbs brand gained less weight, the system of hypothesis would be:

Null hypothesis: $\mu_{1}-\mu_{2}=0$

Alternative hypothesis: $\mu_{1} - \mu_{2}< 0$

The statistic would be given by:

$z=\frac{(\bar X_{1}-\bar X_{2})-\Delta}{\sqrt{\frac{\sigma^2_{1}}{n_{1}}+\frac{\sigma^2_{2}}{n_{2}}}}$ (1)

Replacing the info given we got:

$z=\frac{(7.6-8.1)-0}{\sqrt{\frac{2.3^2}{40}+\frac{2.9^2}{55}}}}=-0.936$

The p value can be founded with this formula:

$p_v =P(z$

Since the p value is higher than the significance level provided of 0.05 we have enough evidence to FAIL to reject the null hypothesis and we can't conclude that the true mean for the Gibbs brand is significantly lower than the true mean for the competitor

5 0

2 years ago