Lambda equals on over pi r squared n.

λ等于πr的n次方。

Lambda equals one over pi r squared n.

λ等于πrn平方分之一。

1 minus lambda over n to the n times 1 minus lambda over n to the minus k.

1 minus lambda over n to the n times 1 减去 lambda over n 减去 k。

Perhaps lambda equals " h" divided by " m" times a velociraptor.

说不定λ等于h除以m乘以迅猛龙。

So it'd be lambda over 60 to the number of successes we need.

所以 lambda 超过 60 就是我们需要的成功次数。

So our probability of success is lambda times n.

所以我们成功的概率是 lambda 乘以 n。

Although using totally different mathematics, they were functionally equivalent to lambda calculus in terms of their computational power.

尽管使用完全不同的数学，但就计算能力而言，它们在功能上等同于 lambda 演算。

Lambda particles, for instance, can have one charm or one strange quark alongside an up and a down.

例如，Lambda 粒子可以有一个魅力或一个奇夸克以及一个上下。

When lambda equals one, the matrix a minus Lambter times the identity, squishes space onto a line.

当=1时 矩阵a-乘以单位矩阵 将空间挤压到一条直线上。

The sweet spot might be hit at some other value of lambda.

最佳点可能在其他的值处。

So times lambda to the k k over k factorial.

所以乘以 lambda 到 k k 阶乘。

Now imagine tweaking lambda turning a knob to change its value.

现在想象一下调整lambda转动旋钮来改变它的值。

So maybe we could say lambda cars per hour is equal to-- I don't know.

所以也许我们可以说每小时的 lambda 汽车等于——我不知道。

And think about subtracting off a variable amount lambda from each diagonal entry.

考虑从每个对角线元素中减去一个变量量。

In this case, the sweet spot comes when lambda equals one.

在这种情况下 最佳点出现在=1时。

We have a minus lambda instead of an a.

我们有一个负 lambda 而不是 a。

That's exactly what we have you here, but instead of an a we have a minus lambda.

这正是我们在这里为您提供的，但我们有一个负 lambda 而不是 a。

So this is going to be equal to e to the minus lambda.

所以这将等于 e 减去 lambda。

The columns of such a matrix will represent what happens to each basis factor, and each basis factor is simply multiplied by lambda.

这样一个矩阵的列将表示每个基因子发生了什么 每个基因子简单地乘以。

1 minus lambda over n to the minus k power.

1 减去 n 的 lambda 的负 k 次方。