When comparing the height and weight of the experimental and control groups, a t-test can be used to determine whether there is a significant difference between the two groups. The calculation of the t-value requires the following steps:

1. Collect the height and weight data of the experimental and control groups.

2. Calculate the mean (\ bar {x}) and standard deviation (s) for each group.

3. Calculate the t-value:

t =\ frac {\ bar {x_1} -\ bar {x_2}} {s_p\ sqrt {\ frac {1} {n_1} \ frac {1} {n_2}}}

where\ bar {x_1} and\ bar {x_2} are the mean of the experimental and control groups, respectively, s_p are the combined standard deviation, and n_1 and n_2 are the sample sizes of the experimental and control groups, respectively.

4. Look up the t-value table and determine the critical value according to the degrees of freedom (df = n_1 n_2 -2) and the significance level (usually 0.05 or 0.01).

5. If the calculated t-value is greater than or equal to the critical value, the Null hypothesis is rejected, that is, there is a significant difference between the two groups; if the t-value is less than the critical value, the Null hypothesis is accepted, that is, there is no significant difference between the two groups.

Please note that before performing the t-test, it is necessary to ensure that the data satisfy the assumption of normal distribution. If the data does not satisfy the normal distribution, the non-parametric test method can be considered. In addition, the above steps only provide a brief method for calculating the t-value, and the specific calculation process may vary depending on the actual situation. It is recommended to refer to relevant statistical books or use statistical software to calculate the t-value when conducting statistical analysis.

** Someone put bats in a room with mosquitoes for experiments. The bats originally weighed 3.9 grams… **

3.9 ÷ 0.002