91影视

The given data is

The number of eggs not hatched is the number of eggs decreased by the number of eggs that hatched.

The proportions in each group is the number of eggs divided by the row total given in the last column:

We can see that the fraction is lowest in cold water, confirming the researcher's hypothesis. However, this percentage is still quite high.

The given data is

Observed counts

The expected counts are the row total multiplied by the column total, divided by the sample size$187$.

The chi-square statistic is the sum of squared deviations (between observed and expected counts) divided by the expected count:

localid="1650643863502" $$\begin{gathered} {蠂}^2=\frac{(16-18.6257{)}^2}{18.6257}+\frac{(11-8.3743{)}^2}{8.3743}+\frac{(38-38.631{)}^2}{38.631}+\frac{(18-17.369{)}^2}{17.369} \\ +\frac{(75-71.7433{)}^2}{71.7433}+\frac{(29-32.2567{)}^2}{32.2567} \\ =1.703 \end{gathered}$$

The interval for the P-value can then be in found in table C in the column title which have the $X^2$-value in the corresponding interval in the row with

localid="1650643872824" $$\begin{gathered} df=(c-1)(r-1) \\ =(3-1)(2-1) \\ =2 \end{gathered}$$

$P>0.25$

If the P-value is smaller than the significance level, then the null hypothesis is rejected

$P>0.05鈬�Failtoreject{H}_0$

There is not sufficient evidence that there is an association between the variables.