In juneau, alaska, the 30-year annual snowfall average is 86.7 inches with a standard deviation of 40.4 inches. the last four years saw an average annual snowfall of 115.7 inches, 62.9 inches, 168.5 inches, and 135.7 inches. hia performs a hypothesis test on this data to determine if the next 30-year norm will have a different average if the trend from the last four years continues. she uses a significance level of 5%. which of the following is a conclusion that she may make?
a) the z-statistic is 1.44, so the null hypothesis cannot be rejected.
b) he z-statistic is 1.68, so the null hypothesis cannot be rejected.
c) the z-statistic is 1.85, so the null hypothesis should be rejected.
d) the z-statistic is 4.6, so the null hypothesis should be rejected.

The expected value of the amount of average snowfall for over 30 years is 86.7 inches with a standard deviation of 40.4 inches. To verify if this particular trend continues, we must check the significance value of the amount snowfall for the past four years. Given that the snowfall for past years are as follows: 115.7 inches, 62.9 inches, 168.5 inches, and 135.7 inches. Thus the mean of the sample would be: (115.7 + 62.9 + 168.5 + 135.7)/4 = 120.7 inches. To compute for the z-score, we have z-score = (x – μ) / (σ / √n) where x is the computed/measured value, μ is the expected mean, σ is the standard deviation, and n is the number of samples. Using the information we have, z-score (z) = (120.7 - 86.7) / (40.4/ √4) = 1.68 In order to reject the null hyptohesis our probability value must be less than the significance level of 5%. For our case, since z = 1.68, P-value = 0.093 > 0.05. Therefore, the answer is B.

Not sure what the question is but i hope this x = years100 * x