For each voter, there are only two possible outcomes. Either the voter is a Democrat, or he is not. The probability of the voter being a Democrat is independent of other voters. So we use the binomial probability distribution to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$

In which $C_{n,x}$ is the number of different combinations of x objects from a set of n elements, given by the following formula.

$C_{n,x} = \frac{n!}{x!(n-x)!}$

And p is the probability of X happening.

62% of the voters are Democrats

This means that $p = 0.62$

(a) What is the probability that two independently surveyed voters would both be Democrats?

This is P(X = 2) when n = 2. So

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$

$P(X = 2) = C_{2,2}.(0.62)^{2}.(0.38)^{0} = 0.3844$

0.3844 = 38.44% probability that two independently surveyed voters would both be Democrats

3 0

3 years ago

What laws being modeled?

ELEN [110]

Answer:

law of contrapositive

Step-by-step explanation:

7 0

3 years ago

Nationally, patients who go to the emergency room wait an average of 7 hours to be admitted into the hospital. Do patients at ru

valina [46]

For this study, we should use t-test and the null and alternative hypotheses would be given by H₀: μ = 7 and H₁: μ < 7.
The test statistic is -1.941 and the p-value (0.0381) is <u>greater than</u> α = 0.01.
Based on this, we should <u>fail to reject</u> the null hypothesis.
Thus, the final conclusion is that the data suggest the population mean is not significantly lower than 7 at α = 0.01, so there is statistically insignificant evidence to conclude that the population mean waiting time to be admitted into the hospital from the emergency room for patients at rural hospitals is equal to 7 hours.

<h3>What is a null hypothesis?</h3>

A null hypothesis (H₀) can be defined the opposite of an alternate hypothesis (H₁) and it asserts that two (2) possibilities are the same.

<h3>How to calculate value of the test statistic?</h3>

The test statistics can be calculated by using this formula:

$t=\frac{x\;-\;u}{\frac{\delta}{\sqrt{n} } }$

<u>Where:</u>

x is the sample mean.

u is the mean.

is the standard deviation.

n is the number of hours.

For this study, we should use t-test and the null and alternative hypotheses would be given by:

H₀: μ = 7

H₁: μ < 7

$t=\frac{6.3\;-\;7}{\frac{1.3}{\sqrt{13} } }\\\\t=\frac{-0.7}{\frac{1.3}{3.6056 } }$

t = -0.7/0.3606

t = -1.941.

For the p-value, we have:

P-value = P(t < -1.9412)

P-value = 0.0381.

Therefore, the p-value (0.0381) is <u>greater than</u> α = 0.01. Based on this, we should <u>fail to reject</u> the null hypothesis.

Thus, the final conclusion is that the data suggest the population mean is not significantly lower than 7 at α = 0.01, so there is statistically insignificant evidence to conclude that the population mean waiting time to be admitted into the hospital from the emergency room for patients at rural hospitals is equal to 7 hours.

Read more on null hypothesis here: brainly.com/question/14913351

#SPJ1

4 0

2 years ago