Whats 10293 x 384? Its really hard!

Answers

Answer 1

Answer:

Answer:

3,952,512

Step-by-step explanation:

Related Questions

Rewrite the function by completing the square.f(x) = x^2 – 10x—96
PLEASE HELP!!! PLATO ALGEBRA 2
A triangle has a base of 16 inches and a height of 18 1 8 inches. What is its area?
Given h(x)= -5x+3,solve for x when h(x)=3
Of all postsecondary degrees awarded in the United States, including master's and doctorate degrees, 21% are associate's degrees, 58% are earned by people whose race is White, and 12% are associate's degrees earned by Whites. What is the conditional probability that a degree is earned by a person whose race is White, given that it is an associate's degree

A probability model includes p(red)=2/7 and P(blue)=3/14. Select all the probabilities that could complete the model.Answer Key:
A: P(green)= 2/7, P(yellow)=2/7
B: P(green)=3/8, P(yellow)=1/8
C: P(green)=1/4 P(yellow)=1/4
D: P(green)= 5/21 Pyellow)= 11/21 E. P(green)= 3/7 P(yellow)=1/14

Answers

Answer:

The answer is "Option D".

Step-by-step explanation:

In this question, the shape of the model is not declared that why we assume that it has four sides in which two sides are given that is:

$\to P(red)=(2)/(7) \n\n\to P(blue)=(3)/(14)$

other probabilities are:

$\to P(green)= (5)/(21) \n\n\to P(yellow)= (11)/(21)$

Given f(x) = -4x - 10 and g(x) = x2 + 1 find f(-2) + g(3).

Answers

The answer to the question

90 percent confidence interval for the proportion difference p1−p2 was calculated to be (0.247,0.325). Which of the following conclusions is supported by the interval?A. There is evidence to conclude that p1>p2 because 0.325 is greater than 0.247.
B. There is evidence to conclude that p1C.There is evidence to conclude that p1>p2 because all values in the interval are positive.
D. There is evidence to conclude that p1E. There is evidence to conclude that p2>p1 because 0.247 and 0.325 are both greater than 0.05.

Answers

You can use the fact that the 90% confidence interval given is all positive value for the test statistic being the difference of $p_1$ and $p_2$ .

The conclusion that is supported by the given confidence interval is given by:

Option C: There is evidence to conclude that $p_1 > p_2$ because all values in the interval are positive.

How can we conclude that there is evidence that $p_1 > p_2$ ?

Since it is given that the difference is measured by $p_1 - p_2$ ,

and since the given confidence interval at 90% confidence for that difference is obtained to be (0.247,0.325), thus we can say that 90% difference value of $p_1 - p_2$ , will be lying in that given interval.

Since the interval is all positive, thus we can say that 90% of the times, the difference $p_1 - p_2$ will be positive which indicates that $p_1 > p_2$

Thus, the conclusion that is supported by the interval is given by:

Option C: There is evidence to conclude that $p_1 > p_2$ because all values in the interval are positive.

Learn more about confidence interval here:

brainly.com/question/14562078

Answer:

Step-by-step explanation:

Statistics!!

When we have a confidence interval for the difference in proportions or means, our null hypothesis is always that there's no difference. (H0 = p1-p2 = 0.)

If the difference is positive, that means we have sufficient evidence p1>p2.

If it's negative, then we have sufficient evidence p2>p1.

Why not A: incorrect interpretation of the interval

Why not B: doesn't look like a complete answer

Why not D: also doesn't look like a complete answer

Why not E: this confuses the definition of alpha-level and p-value with confidence interval values. If those were p-values and greater or less than an alpha-level, we would reject or fail to reject the null hypothesis. That isn't the case here.

A true/false test has 90 questions. Suppose a passing grade is 58 or more correct answers. Test the claim that a student knows more than half of the answers and is not just guessing. Assume the student gets 58 answers correct out of 90. Use a significance level of 0.05. Steps 1 and 2 of a hypothesis test procedure are given below. Show step 3, finding the test statistic and the p-value and step 4, interpreting the results.

Answers

Answer:

1 and 2) Null hypothesis: $p \leq 0.5$

Alternative hypothesis: $p > 0.5$

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

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

3) $z=\frac{0.644 -0.5}{\sqrt{(0.5(1-0.5))/(90)}}=2.732$

4) $p_v =P(z>2.732)=0.0031$

So the p value obtained was a very low value and using the significance level given $\alpha=0.05$ we have $p_v<\alpha$ so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of correct answers is not significantly higher than 0.5

Step-by-step explanation:

Data given and notation

n=90 represent the random sample taken

X=58 represent the number of correct answers

$\hat p=(58)/(90)=0.644$ estimated proportion of correct answers

$p_o=0.5$ 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)

Step 1 and 2: Concepts and formulas to use

We need to conduct a hypothesis in order to test the claim that the true proportion of correct answers is higher than 0.5.:

Null hypothesis: $p \leq 0.5$

Alternative hypothesis: $p > 0.5$

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

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

$z=\frac{0.644 -0.5}{\sqrt{(0.5(1-0.5))/(90)}}=2.732$

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 right tailed test the p value would be:

$p_v =P(z>2.732)=0.0031$

Answer:

Step-by-step explanation:

Hello!

The variable of interest is X: the number of correct answers on a true/false test out of 90 questions.

The parameter of interest is p: population proportion of correct answers in a true/false test.

The passing grade is 58/90 correct questions.

The claim is that if the students answer more than half of the answers, then he is not guessing, i.e. if the proportion of correct answers is more than 50%, the student did not guess the answers, symbolically: p>0.5

Then the hypotheses are:

H₀: p ≤ 0.5

H₁: p > 0.5

α: 0.05

since the sample size is large enough, n= 90 questions, you can apply the Central Limit Theorem to approximate the distribution of the sample proportion to normal, p'≈N(p;[p(1-p])/n) and use the standard normal as a statistic:

$Z=\frac{p'-p}{\sqrt{(p(1-p))/(n) } }$ ≈N(0;1)

The sample proportion is the passing grade of the student p': 58/90= 0.64

Then under the null hypothesis the statistic is:

$Z_(H_0)= \frac{0.64-0.5}{\sqrt{(0.5*0.5)/(90) } } = 2.656= 2.66$

This test is one-tailed (right) and so is the p-value, you can calculate it as:

P(Z≥2.66)= 1 - P(Z<2.66)= 1 - 0.996093= 0.003907

With this p-value, the decision is to reject the null hypothesis.

Then at a 5% level, there is significant evidence to conclude that the proportion of correctly answered questions is greater than 50%, this means that the student didn't guess the answers.

I hope this helps!

Weights of men: 90% confidence; n = 14, x=161.5 lb, s =13.7 lb

Answers

Answer:

The 90% for the average weights of men is between 137.24 lb and 185.76 lb.

Step-by-step explanation:

We have the standard deviation for the sample, so we use the t-distribution to solve this question.

The first step to solve this problem is finding how many degrees of freedom, we have. This is the sample size subtracted by 1. So

df = 14 - 1 = 14

90% confidence interval

Now, we have to find a value of T, which is found looking at the t table, with 14 degrees of freedom(y-axis) and a confidence level of $1 - (1 - 0.9)/(2) = 0.95$ . So we have T = 1.7709

The margin of error is:

M = T*s = 1.7709*13.7 = 24.26

In which s is the standard deviation of the sample.

The lower end of the interval is the sample mean subtracted by M. So it is 161.5 - 24.26 = 137.24 lb

The upper end of the interval is the sample mean added to M. So it is 161.5 + 24.26 = 185.76 lb

The 90% for the average weights of men is between 137.24 lb and 185.76 lb.

A container in a pharmacy holds 0.92 liter of a solution. Mrs. Dwyer used 0.5 of the container for a prescription. How much did she use?A 0.046 liters
B 0.46 liters
C 4.6 liters
D 46 liters