How much is 10% to the power of 2?

This table represents a function plot the points to represent the function as a graph

yKpoI14uk [10]

Answer:

The graph in the attached figure N 2

Step-by-step explanation:

The complete question in the attached figure N 1

we have the ordered pairs

(-4,9),(-1,3),(0,1),(2,-3)

Using a graphing tool

Plot the given ordered pairs in the coordinate plane

Remember that

In a ordered pair (x,y), the first coordinate is the location of the point in the x-axis and the second coordinate is the location of the point in the y-axis

see the attached figure

The graph represent a line

<em>Find the equation of the line</em>

<em>Find the slope</em>

take two points

$(0,1),(2,-3)\\m=(-3-1)/(2-0)=-2$

The equation of the line in slope intercept form is equal to

$y=mx+b$

we have

$m=-2\\b=1$

substitute

$y=-2x+1$

6 0

2 years ago

A movie theater has a seating capacity of 179. The theater charges $5.00 for children, $7.00 for students, and $12.00 of adults.

Semmy [17]

Adult 31
Children 62
Student 86

3 0

2 years ago

Read 2 more answers

1 dollar = 1.2 euros

MArishka [77]

85 yen are equivalent to 1 euro ⇒ answer O

Step-by-step explanation:

The given is:

1 dollar = 1.2 euros
1 dollar = 102 yen

We need to find how many yens are equivalent to 1 euro

∵ 1 dollar = 1.2 euros

∵ 1 dollar = 102 yen

- Equate the two right sides of 1 dollar

∴ 1.2 euros = 102 yen

- To find 1 euro equals how many yen divide both sides by 1.2

∵ (1.2 ÷ 1.2) euros = (102 ÷ 1.2) yen

∴ 1 euro = 85 yen

85 yen are equivalent to 1 euro

Learn more:

You can learn more about the word problems in brainly.com/question/2119883

#LearnwithBrainly

4 0

2 years ago

In March 2015, the Public Policy Institute of California (PPIC) surveyed 7525 likely voters living in California. This is the 14

lbvjy [14]

Answer:

We are confident at 99% that the difference between the two proportions is between $0.380 \leq p_{Republicans} -p_{Democrats} \leq 0.420$

Step-by-step explanation:

Part a

Data given and notation

$X_{D}=3266$ represent the number people registered as Democrats

$X_{R}=2137$ represent the number of people registered as Republicans

$n=7525$ sampleselcted

$\hat p_{D}=\frac{3266}{7525}=0.434$ represent the proportion of people registered as Democrats

$\hat p_{R}=\frac{2137}{7525}=0.284$ represent the proportion of people registered as Republicans

The standard error is given by this formula:

$SE=\sqrt{\frac{\hat p_D (1-\hat p_D)}{n_{D}}+\frac{\hat p_R (1-\hat p_R)}{n_{R}}}$

And the standard error estimated given by the problem is 0.008

Part b

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

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".

$p_A$ represent the real population proportion of Democrats that approve of the way the California Legislature is handling its job

$\hat p_A =\frac{1894}{3266}=0.580$ represent the estimated proportion of Democrats that approve of the way the California Legislature is handling its job

$n_A=3266$ is the sample size for Democrats

$p_B$ represent the real population proportion of Republicans that approve of the way the California Legislature is handling its job

$\hat p_B =\frac{385}{2137}=0.180$ represent the estimated proportion of Republicans that approve of the way the California Legislature is handling its job

$n_B=2137$ is the sample for Republicans

$z$ represent the critical value for the margin of error

The population proportion have the following distribution

$p \sim N(p,\sqrt{\frac{p(1-p)}{n}})$

The confidence interval for the difference of two proportions would be given by this formula

$(\hat p_A -\hat p_B) \pm z_{\alpha/2} \sqrt{\frac{\hat p_A(1-\hat p_A)}{n_A} +\frac{\hat p_B (1-\hat p_B)}{n_B}}$

For the 90% confidence interval the value of $\alpha=1-0.90=0.1$ and $\alpha/2=0.05$ , with that value we can find the quantile required for the interval in the normal standard distribution.