What is the solution of √ x2+49 = x+5

1 3/4 divided by 1/2-1 1/2 to the 3rd

Marina CMI [18]

Answer:

-7/4

1/8

Step-by-step explanation:

1. If the problem is; (1 3/4) / (1/2 - 1 1/2)^(3)

(a). Convert to improper fractions;

(7/4) / (1/2 - 3/2)^3

(b). Simplify;

(7/4) / (-2/2)^3

(7/4) / (-1)^3

(7/4) / (-1)

-7/4

2. If the problem is; ((1 3/4) / (1/2)) - (1 1/2)^3

(a). Convert to improper fractions;

((7/4)/ (1/2)) - (3/2)^3

(b). Simplify;

((7/4)/ (1/2)) - (3/2)^3

((7/4)*(2/1)) - (27/8)

(7/2) - (27/8)

(28/8) - (27/8)

1/8

6 0

3 years ago

Match each polynomial expression to is additive inverse

andriy [413]

Answer:

hope you get it ........

3 0

3 years ago

What is the decimal equivalent of each rational number?

NeX [460]

where is the question you want answered

3 0

3 years ago

Add the them a. 2x2 – 3y2 , 5x2 + 6y2, - 3x2 – 4y2

soldier1979 [14.2K]

=
−
3
x
2
y
25
+
6
x
2
y
23
+
2
x
2
−
4
y
2

5 0

3 years ago

in a program designed to help patients stop smoking 232 patients were given sustained care and 84.9% of them were no longer smok

grandymaker [24]

Answer:

$z=\frac{0.849 -0.8}{\sqrt{\frac{0.8(1-0.8)}{232}}}=1.869$

$p_v =2*P(Z>1.869)=0.0616$

If we compare the p value obtained and the significance level given $\alpha=0.05$ we see that $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of adults were no longer smoking after one month is not significantly different from 0.8 or 80% .

Step-by-step explanation:

1) Data given and notation

n=232 represent the random sample taken

X represent the adults were no longer smoking after one month

$\hat p=0.849$ estimated proportion of adults were no longer smoking after one month

$p_o=0.80$ is the value that we want to test

$\alpha=0.05$ represent the significance level

Confidence=95% or 0.95

z would represent the statistic (variable of interest)

$p_v$ represent the p value (variable of interest)

2) Concepts and formulas to use

We need to conduct a hypothesis in order to test the claim that the true proportion is 0.8.:

Null hypothesis: $p=0.8$

Alternative hypothesis: $p \neq 0.8$

When we conduct a proportion test we need to use the z statistic, and the is given by:

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$ (1)

The One-Sample Proportion Test is used to assess whether a population proportion $\hat p$ is significantly different from a hypothesized value $p_o$ .

3) Calculate the statistic

Since we have all the info requires we can replace in formula (1) like this:

$z=\frac{0.849 -0.8}{\sqrt{\frac{0.8(1-0.8)}{232}}}=1.869$

4) Statistical decision

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.

The significance level provided $\alpha=0.05$ . The next step would be calculate the p value for this test.

Since is a bilateral test the p value would be:

$p_v =2*P(Z>1.869)=0.0616$

If we compare the p value obtained and the significance level given $\alpha=0.05$ we see that $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of adults were no longer smoking after one month is not significantly different from 0.8 or 80% .

6 0

4 years ago