另外一种方法就是用链式法则。
可以用链式法则来回答这个问题。
Well, we can answer that. The chain rule is something like this.
把链式法则用在多个变量中。
根据链式法则，我得到θ点。
这在链式法则里面看到过。
这就是所谓的“链式法则”
链式法则告诉了我们什么？
这里我们利用链式法则。
考虑链式法则，还应该再乘以恒定的温度下的。
可以使用链式法则。
我们可以用微分，就像这样，也可以用链式法则。
Well, we could use differentials, like we did here, but we can also keep using the chain rule.
我们推导链式法则的过程中有一个漏洞。
要用链式法则。
我们当然知道答案了,因为这是链式法则的一个特例。
Well, of course we know the answer because that's a special case of the chain rule.
我们还学过微分的链式法则，也就是用其他量来代替这些偏导数。
So, we've learned about differentials and chain rules, which are a way of repackaging these partial derivatives.
为了把这里的p变成,我们需要利用链式法则,好，让我们使用链式法则。
这一关系只对理想气体成立，上节课我们，用链式法则推导出了这一关系。
OK, this is only true for an ideal gas, and we went through that mathematically where the, with a chain rule.
用函数的链式法则和乘积公式给出了参数函数和复合函数的高阶导数的计算公式。
The formulas calculating higher derivatives of parametric functions and composite functions are given by the chain rule and the product formula for derivatives.
我们可以从限制条件中找到这个，我们一开始就看到的，要么用微分限制条件，要么利用链式法则。
OK, and we can find this one from the constraints as we've een at the beginning either by differentiating the constraint, or by using the chain rule on the constraint.
有一个极值问题，也有关于拉格朗日乘数法的，链式法则也会有的,约束条件下偏导数当然不会漏掉。
Expect one about a min/max problem, something about Lagrange multipliers, something about the chain rule and something about constrained partial derivatives.
有一个极值问题，也有关于拉格朗日乘数法的，链式法则也会有的,约束条件下偏导数当然不会漏掉。
Expect one about a min/max problem, something about Lagrange multipliers, something about the chain rule and something about constrained partial derivatives.
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