Probstat/week14 practice 1 - ประวัติรุ่นแก้ไข

Jittat: /* Least square estimators */

2014-11-27T01:14:07Z

Least square estimators

2014-11-25T03:21:47Z

2014-11-25T03:21:26Z

2014-11-25T01:58:38Z

Least square estimators

2014-11-25T01:58:24Z

Least square estimators

2014-11-25T01:57:31Z

Least square estimators

2014-11-25T01:55:34Z

Least square estimators

2014-11-25T01:51:10Z

Least Square Estimators

2014-11-25T01:50:15Z

หน้าที่ถูกสร้างด้วย '== Least Square Estimators == == Multiple linear regression =='

หน้าใหม่

== Least Square Estimators ==

== Multiple linear regression ==

@@ แถว 12: / แถว 12: @@
 * Give the data to your partner.
-* After you get the data from your friend, find the least square estimators for <math>\alpha</math> and <math>\beta</math>.
+* After you get the data from your friend, find the least square estimators ''A'' and ''B'' for <math>\alpha</math> and <math>\beta</math>.
 * Ask for the correct parameters and see how close you get to those parameters as we increase the size of the samples <math>n</math>.

←รุ่นแก้ไขก่อนหน้า		รุ่นแก้ไขเมื่อ 03:21, 25 พฤศจิกายน 2557
แถว 1:		แถว 1:
		+	: ''This is part of [[probstat]]''.
		+
	== Least square estimators ==		== Least square estimators ==
	1. You should work in pairs. Try the following for <math>n=3, 5, 20, 100</math>		1. You should work in pairs. Try the following for <math>n=3, 5, 20, 100</math>

←รุ่นแก้ไขก่อนหน้า		รุ่นแก้ไขเมื่อ 03:21, 25 พฤศจิกายน 2557
แถว 15:		แถว 15:

	== Multiple linear regression ==		== Multiple linear regression ==
		+	Follow the same procedure as in the previous section, but try with 2 variables <math>x_1</math> and <math>x_2</math>. I.e., you pick parameter <math>\alpha, \beta_1, \beta_2</math> and generate samples from the following formula
		+
		+	<center><math>Y = \alpha + \beta_1 x_1 + \beta_2 x_2 + e</math>.</center>

@@ แถว 12: / แถว 12: @@
 * After you get the data from your friend, find the least square estimators for <math>\alpha</math> and <math>\beta</math>.
-* Ask for the correct parameters and see how close you get to those parameters as we increase the value of <math>n</math>.
+* Ask for the correct parameters and see how close you get to those parameters as we increase the size of the samples <math>n</math>.
 == Multiple linear regression ==

@@ แถว 10: / แถว 10: @@
 * Give the data to your partner.
-* After you get the data from your friend, find the least square estimators for <math>\alpha</math> and <math>\beta</math>
+* After you get the data from your friend, find the least square estimators for <math>\alpha</math> and <math>\beta</math>.
 == Multiple linear regression ==

←รุ่นแก้ไขก่อนหน้า		รุ่นแก้ไขเมื่อ 01:57, 25 พฤศจิกายน 2557
แถว 5:		แถว 5:

	<center><math>Y = \alpha + \beta x + e</math></center>		<center><math>Y = \alpha + \beta x + e</math></center>
		+
		+	Use random values for <math>x</math> in the range that you like. For the error <math>e</math>, you can generate a random error based on a normal distributions.
		+
		+	* Give the data to your partner.
		+
		+	* After you get the data from your friend, find the least square estimators for <math>\alpha</math> and <math>\beta</math>

	== Multiple linear regression ==		== Multiple linear regression ==

←รุ่นแก้ไขก่อนหน้า		รุ่นแก้ไขเมื่อ 01:55, 25 พฤศจิกายน 2557
แถว 1:		แถว 1:
	== Least square estimators ==		== Least square estimators ==
		+	1. You should work in pairs. Try the following for <math>n=3, 5, 20, 100</math>
		+
		+	* First, you pick a parameter <math>\alpha</math> and <math>\beta</math> and generate a sample of size <math>n</math> using the formula:
		+
		+	<center><math>Y = \alpha + \beta x + e</math></center>

	== Multiple linear regression ==		== Multiple linear regression ==