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Say we have a sample with a bunch of the original stuff, and you can see when each of them decays. One of them will take $t_1$, another $t_2$, another... If we calculate the average of those, we get a time called 'average life', usually denoted by the greek letter $\tau$:

$\tau = \frac{\sum_i t_i}{N}$

If the sample is big enough, the number of decays we see in a time interval $dt$ is (*)

$ N\frac{dt}{\tau} $,

or, in terms of change in the number of undecayed nuclei,

$ dN=-N \frac{dt}{\tau} $.

If you solve the differential equation, you get:

$ \frac{dN}{dt} = -\frac{N}{\tau} \Rightarrow N(t)=N_0 e^{-t/\tau} $

Which, comparing to yours,

$ N(t)=N_0 e^{-t/\tau}=N_0 e^{-\lambda t} \Rightarrow \lambda = \frac{1}{\tau} $

(*) I know this is overly simplified, but you would probably have to work from Poisson statistics up to really justify this.

Edit: to better answer question 1, let's have a look at the activity by derivating the number of particles not yet disintegrated, $ N(t) $:

$ A(t) = - \frac{dN}{dt} = - \frac{d}{dt} \left( N_0 e^{-\lambda t} \right) = \lambda N_0 e^{-\lambda t} = \lambda N(t) $

So $ \lambda $, besides being the reciprocal of the average life, also links activity and number of radioactive particles.

Say we have a sample with a bunch of the original stuff, and you can see when each of them decays. One of them will take $t_1$, another $t_2$, another... If we calculate the average of those, we get a time called 'average life', usually denoted by the greek letter $\tau$:

$\tau = \frac{\sum_i t_i}{N}$

If the sample is big enough, the number of decays we see in a time interval $dt$ is (*)

$ N\frac{dt}{\tau} $,

or, in terms of change in the number of undecayed nuclei,

$ dN=-N \frac{dt}{\tau} $.

If you solve the differential equation, you get:

$ \frac{dN}{dt} = -\frac{N}{\tau} \Rightarrow N(t)=N_0 e^{-t/\tau} $

Which, comparing to yours,

$ N(t)=N_0 e^{-t/\tau}=N_0 e^{-\lambda t} \Rightarrow \lambda = \frac{1}{\tau} $

(*) I know this is overly simplified, but you would probably have to work from Poisson statistics up to really justify this.

Say we have a sample with a bunch of the original stuff, and you can see when each of them decays. One of them will take $t_1$, another $t_2$, another... If we calculate the average of those, we get a time called 'average life', usually denoted by the greek letter $\tau$:

$\tau = \frac{\sum_i t_i}{N}$

If the sample is big enough, the number of decays we see in a time interval $dt$ is (*)

$ N\frac{dt}{\tau} $,

or, in terms of change in the number of undecayed nuclei,

$ dN=-N \frac{dt}{\tau} $.

If you solve the differential equation, you get:

$ \frac{dN}{dt} = -\frac{N}{\tau} \Rightarrow N(t)=N_0 e^{-t/\tau} $

Which, comparing to yours,

$ N(t)=N_0 e^{-t/\tau}=N_0 e^{-\lambda t} \Rightarrow \lambda = \frac{1}{\tau} $

(*) I know this is overly simplified, but you would probably have to work from Poisson statistics up to really justify this.

Edit: to better answer question 1, let's have a look at the activity by derivating the number of particles not yet disintegrated, $ N(t) $:

$ A(t) = - \frac{dN}{dt} = - \frac{d}{dt} \left( N_0 e^{-\lambda t} \right) = \lambda N_0 e^{-\lambda t} = \lambda N(t) $

So $ \lambda $, besides being the reciprocal of the average life, also links activity and number of radioactive particles.

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Say we have a sample with a bunch of the original stuff, and you can see when each of them decays. One of them will take $t_1$, another $t_2$, another... If we calculate the average of those, we get a time called 'average life', usually denoted by the greek letter $\tau$:

$\tau = \frac{\sum_i t_i}{N}$

If the sample is big enough, the number of decays we see in a time interval $dt$ is (*)

$ N\frac{dt}{\tau} $,

or, in terms of change in the number of undecayed nuclei,

$ dN=-N \frac{dt}{\tau} $.

If you solve the differential equation, you get:

$ \frac{dN}{dt} = -\frac{N}{\tau} \Rightarrow N(t)=N_0 e^{-t/\tau} $

Which, comparing to yours,

$ N(t)=N_0 e^{-t/\tau}=N_0 e^{-\lambda t} \Rightarrow \lambda = \frac{1}{\tau} $

(*) I know this is overly simplified, but you would probably have to work from Poisson statistics up to really justify this.