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Calcium is essential to tree growth. In 1990, the concentration of calcium in precipitation in Chautauqua, New York, was 0.11 milligram per liter $\left(\frac{\mathrm{mg}}{\mathrm{L}}\right)$. A random sample of 8 precipitation dates in 2018 results in the following data:

A normal probability plot suggests the data could come from a population that is normally distributed. A boxplot does not show any outliers. Does the sample evidence suggest that calcium concentrations have changed since 1990 ? Use the $a=0.01$ level of significance.

What are the null and alternative hypotheses?
$H_{0} \cdot \mu=11$
$H_{1}=\mu \neq .11$
(Type integers or decimals. Do not round.)
Find the test statistic
$t_{0}=1.31$ (Round to two decimal places as needed.)

Step 1 ：The null hypothesis (H0) and alternative hypothesis (H1) are incorrectly stated in the question. They should be: H0: μ = 0.11 (The mean calcium concentration in 2018 is the same as in 1990) H1: μ ≠ 0.11 (The mean calcium concentration in 2018 is not the same as in 1990) The test statistic (t0) is given as 1.31. This value is used to determine whether we reject or fail to reject the null hypothesis. To make this decision, we compare the test statistic to the critical value at the given level of significance (α = 0.01). For a two-tailed test with 7 degrees of freedom (n-1 = 8-1 = 7), the critical values are approximately ±2.998. Since the test statistic (1.31) is less than the critical value (2.998), we fail to reject the null hypothesis. This means that we do not have enough evidence to conclude that the mean calcium concentration in 2018 is different from that in 1990. In summary, based on the sample data and the given level of significance, there is not enough evidence to suggest that calcium concentrations have changed since 1990.