The probable number of prople sent to US emergency rooms by 2090 can be between 22,050 and 23,100
Step-by-step explanation:
Total sent to US emergency room by 2010= 21000
The estimated increase in the rise of cases = 5 to 10% by 2090
Final numbers in 2090
Hence the final numbers in 2090 would be 5 to 10% more than the total cases in 2010
Lower limit= 5% of 21000= 1050
Hence lower limit of cases in 2090= 21000+1050= 22050
Upper limit of cases in 2090= 10% of 21000= 21000+2100= 23,100
The number would lie anywhere between 22050 and 23,100 in 2090
Answer:
6 ounces of juice
Step-by-step explanation:
<span>There are 8,904 cycles per minute. This would be determining the amount of cycles per second, which is 148.4. After you know the amount per second, you can then multiply it by the time, which in this case is 60 seconds, or 1 minute. 148.4 cycles per second multiplied by 60 seconds is 8,904 cycles.</span>
Answer:
so you can simplify the ratio
Step-by-step explanation:
Answer and Step-by-step explanation:
This is a complete question
Trials in an experiment with a polygraph include 97 results that include 23 cases of wrong results and 74 cases of correct results. Use a 0.01 significance level to test the claim that such polygraph results are correct less than 80% of the time. Identify the nullhypothesis, alternative hypothesis, test statistic, P-value, conclusion about the null hypothesis, and final conclusion that addresses the original claim. Use the P-value method. Use the normal distribution as an approximation of the binomial distribution.
The computation is shown below:
The null and alternative hypothesis is



= 0.7629
Now Test statistic = z
![= \hat p - P0 / [\sqrtP0 \times (1 - P0 ) / n]](https://tex.z-dn.net/?f=%3D%20%5Chat%20p%20-%20P0%20%2F%20%5B%5CsqrtP0%20%5Ctimes%20%281%20-%20P0%20%29%20%2F%20n%5D)
![= 0.7629 - 0.80 / [\sqrt(0.80 \times 0.20) / 97]](https://tex.z-dn.net/?f=%3D%200.7629%20-%200.80%20%2F%20%5B%5Csqrt%280.80%20%5Ctimes%200.20%29%20%2F%2097%5D)
= -0.91
Now
P-value = 0.1804


So, it is Fail to reject the null hypothesis.
There is ample evidence to demonstrate that less than 80 percent of the time reports that these polygraph findings are accurate.