ผลต่างระหว่างรุ่นของ "Week11 practice 2"
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Jittat (คุย | มีส่วนร่วม) |
Jittat (คุย | มีส่วนร่วม) (→Sample) |
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แถว 1: | แถว 1: | ||
== Sample == | == Sample == | ||
− | Suppose that you take <math>n</math> samples <math>X_1,X_2,\ldots,X_n</math> independently from | + | Consider a certain distribution. The mean <math>\mu</math> of the distribution is the expected value of a random variable <math>X</math> sample from the distribution. I.e., |
+ | |||
+ | <center> | ||
+ | <math>\mu=E[X]</math>. | ||
+ | </center> | ||
+ | |||
+ | Also recall that the variance of the distribution is | ||
+ | |||
+ | <center> | ||
+ | <math>\sigma^2=Var(X)=E[(X-\mu)^2]=E[X^2] = E[X]^2.</math>. | ||
+ | </center> | ||
+ | |||
+ | And finally, the standard deviation is <math>\sigma = \sqrt{Var(X)}</math>. | ||
+ | |||
+ | Suppose that you take <math>n</math> samples <math>X_1,X_2,\ldots,X_n</math> independently from this distribution. (Note that <math>X_1,X_2,\ldots,X_n</math> are random variables. | ||
=== Sample means === | === Sample means === | ||
แถว 11: | แถว 25: | ||
is called a '''sample mean.''' | is called a '''sample mean.''' | ||
+ | |||
+ | We can compute: | ||
+ | |||
+ | <math>E[\bar{X}]= E\left[\frac{1}{n}\sum_{i=1}^n X_i\right] = \frac{1}{n} | ||
=== Sample variances and sample standard deviations === | === Sample variances and sample standard deviations === |
รุ่นแก้ไขเมื่อ 01:34, 6 พฤศจิกายน 2557
Sample
Consider a certain distribution. The mean of the distribution is the expected value of a random variable sample from the distribution. I.e.,
.
Also recall that the variance of the distribution is
.
And finally, the standard deviation is .
Suppose that you take samples independently from this distribution. (Note that are random variables.
Sample means
The statistic
is called a sample mean.
We can compute:
<math>E[\bar{X}]= E\left[\frac{1}{n}\sum_{i=1}^n X_i\right] = \frac{1}{n}