XY=11d\ YZ=9d-2\ \ xz=5a+22

What is the measure of LXZW? 850 150° Y 65° 95 Z 215° W 30°

Semenov [28]

Answer:

so the answer is 95°

Step-by-step explanation:

The two angles on a line add up to 180° or are supplementary, so we can find the inside angle x by doing 180-150=30°. Now that we know inside x is 30, if we add 30+65, we get 95, and 180-95=85°. Then to find angle xzw, just do 180-85 to get 95°.

3 0

3 years ago

Any and all help would be appreciated!

SpyIntel [72]

The way we can find out the unit rate (also known as the SLOPE) is by using the table as coordinates!

The slope formula is $\frac{y2 - y1}{x2 -x1}$

With the table, the TIME column can be "x"

The DISTANCE column can be "y"

____________________________

As coordinates, it would look like...

(0,0)

(20, 25)

(30, 37.5) and so on!

_____________________________

All we need to do now is use 2 of these coordinates and plug them into the slope formula in their correct places to find the unit rate!

Example:

solve!

$\frac{37.5 - 25}{30 - 20}$ = 12.5/10 ⇒ 1.25 ( or 5/4 in fraction form)

8 0

3 years ago

Write an equation perpendicular to the line y=3/2x-2 that goes through (-4,3)

Goryan [66]

Answer: y=-2/3x-2/3

Step-by-step explanation:

concept to know: two lines that are perpendicular has opposite reciprocal slopes.

y=-2/3x+b

in order to find b or the y-intercept, we need to plug in a point

3=-2/3(-4)+b

3=8/3+b

b=-2/3

y=-2/3x-2/3

Hope this helps!! :)

4 0

4 years ago

A sample of size 6 will be drawn from a normal population with mean 61 and standard deviation 14. Use the TI-84 Plus calculator.

AVprozaik [17]

Answer:

$X \sim N(61,14)$

Where $\mu=61$ and $\sigma=14$

Since the distribution for X is normal then the distribution for the sample mean is also normal and given by:

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

$\mu_{\bar X} = 61$

$\sigma_{\bar X}= \frac{14}{\sqrt{6}}= 5.715$

So then is appropiate use the normal distribution to find the probabilities for $\bar X$

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean". The letter $\phi(b)$ is used to denote the cumulative area for a b quantile on the normal standard distribution, or in other words: $\phi(b)=P(z$

Solution to the problem

Let X the random variable that represent the variable of interest of a population, and for this case we know the distribution for X is given by:

$X \sim N(61,14)$

Where $\mu=61$ and $\sigma=14$

Since the distribution for X is normal then the distribution for the sample mean $\bar X$ is also normal and given by:

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

$\mu_{\bar X} = 61$

$\sigma_{\bar X}= \frac{14}{\sqrt{6}}= 5.715$

So then is appropiate use the normal distribution to find the probabilities for $\bar X$

8 0

3 years ago

A tire manufacturer is considering a newly designed tread pattern for its all-weather tires. Tests have indicated that these tir

Nataly_w [17]

Answer:

With outlier (102)

$t=\frac{126.2-125}{\frac{9.138}{\sqrt{10}}}=0.415$

$p_v =P(t_{9}>0.415)=0.344$

If we compare the p value and a significance level assumed $\alpha=0.05$ we see that $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so we can conclude that the true mean is not significantly higher than 125 feet at 5% of significance.

Without outlier (102)

$t=\frac{128.89-125}{\frac{3.551}{\sqrt{9}}}=3.285$

$p_v =P(t_{8}>3.285)=0.0056$

And we conclude that we reject the null hypothesis since $p_v$ . So the final conclusion would be not use the method since the value of 102 observed can be a potential outlier, removing this value we see that we reject the null hypothesis and we have a significant result that the true mean is higher than 125.

Step-by-step explanation:

Previous concepts and data given

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

Data: 129, 128, 130, 132, 135, 123, 102, 125, 128, 130

We can calculate the mean with the following formulas:

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

$s=\sqrt{\frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}}$

$\bar X=126.2$ represent the sample mean

$s=9.138$ represent the sample standard deviation

n=10 represent the sample selected

$\alpha$ significance level

State the null and alternative hypotheses.

We need to conduct a hypothesis in order to check if the mean is significantly higher than 125, the system of hypothesis would be:

Null hypothesis: $\mu \leq 125$

Alternative hypothesis: $\mu > 125$

If we analyze the size for the sample is < 30 and we don't know the population deviation so is better apply a t test to compare the actual mean to the reference value, and the statistic is given by:

$t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}}$ (1)

t-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".

Calculate the statistic

We can replace in formula (1) the info given like this:

$t=\frac{126.2-125}{\frac{9.138}{\sqrt{10}}}=0.415$

P-value

First we need to calculate the degrees of freedom given by:

$df=n-1=10-1= 9$

Then since is a right tailed sided test the p value would be:

$p_v =P(t_{9}>0.415)=0.344$

Conclusion

If we compare the p value and a significance level assumed $\alpha=0.05$ we see that $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so we can conclude that the true mean is not significantly higher than 125 feet at 5% of significance.

Using all the data we see that we don;t have enough info to conclude that the true mean is higher than 125, but if we see careful 9 of the 10 values are over the limit of 125 feet. And if we repeat the procedure with the outlier of 102. We got this:

$\bar X=128.89$ represent the sample mean

$s=3.551$ represent the sample standard deviation

$t=\frac{128.89-125}{\frac{3.551}{\sqrt{9}}}=3.285$

First we need to calculate the degrees of freedom given by:

$df=n-1=9-1= 8$

Then since is a right tailed sided test the p value would be:

$p_v =P(t_{8}>3.285)=0.0056$

And we conclude that we reject the null hypothesis since $p_v$ . So the final conclusion would be not use the method since the value of 102 observed can be a potential outlier removing this value we see that we reject the null hypothesis and we have a significant result that the true mean is higher than 125.

8 0

3 years ago