Determine if S could lie on the perpendicular bisector of QR with the given coordinates

Equation of a circle whose center is at (4,0) and radius is length 2/3

Masteriza [31]

We need (x-h)^2 + (y-k)^2 = r^2

h = 4, k = 0 and r = 2/3

Take it from here.

5 0

3 years ago

it is known that the population proton of utha residnet that are members of the church of jesus christ 0l6 suppose a random samp

Lady_Fox [76]

Answer:

0.0838 = 8.38% probability of obtaining a sample proportion less than 0.5.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$

Proportion of 0.6

This means that $p = 0.6$

Sample of 46

This means that $n = 46$

Mean and standard deviation:

$\mu = p = 0.6$

$s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.6*0.4}{46}} = 0.0722$

Probability of obtaining a sample proportion less than 0.5.

p-value of Z when X = 0.5. So

$Z = \frac{X - \mu}{\sigma}$

By the Central Limit Theorem

$Z = \frac{X - \mu}{s}$

$Z = \frac{0.5 - 0.6}{0.0722}$

$Z = -1.38$

$Z = -1.38$ has a p-value of 0.0838

0.0838 = 8.38% probability of obtaining a sample proportion less than 0.5.

8 0

3 years ago

Work out<br> 55<br> % of <br> 2900

riadik2000 [5.3K]

Change 55% to 0.55
0.55 x 2900 = 1595

4 0

3 years ago

Read 2 more answers

Peter bought 9 packs of pencils. Each pack has 10 pencils in it. If he lost 18 pencils, how many pencils

Sindrei [870]

Answer:

a 72

Step-by-step explanation:

9x10=90, so in total he has 90 pencils. if he loses 18 of them that's 90-18 which is 72.

4 0

3 years ago

A shoe manufacturer was investigating the weights of men's soccer cleats. He felt that the weight of these cleats was less than

aleksklad [387]

Answer:

The conclusion is that the researcher was correct

Step-by-step explanation:

From the question we are told that

The sample size is $n = 13$

The sample mean is $\= x = 9.63$

The standard deviation is $s = 0.585$

The significance level is $\alpha = 0.05$

The Null Hypothesis is $H_o : \mu = 0$

The Alternative Hypothesis is $H_a = \mu < 10$

The test statistic is mathematically represented as

$t = \frac{\= x - \mu }{\frac{s}{\sqrt{n} } }$

Substituting values

$t = \frac{9.63 - 10 }{\frac{0.585}{\sqrt{13} } }$

$t = - 2.280$

Now the critical value for $\alpha$ is

$t_{\alpha } = 1.645$

This obtained from the critical value table

So comparing the critical value of alpha and the test value we see that the test value is less than the critical value so the Null Hypothesis is rejected

The conclusion is that the researcher was correct

6 0

3 years ago