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	<title>Statistik 4 Life</title>
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		<title>Statistik 4 Life</title>
		<link>http://ariyoso.wordpress.com</link>
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		<title>Korelasi Biserial</title>
		<link>http://ariyoso.wordpress.com/2011/07/07/korelasi-biserial/</link>
		<comments>http://ariyoso.wordpress.com/2011/07/07/korelasi-biserial/#comments</comments>
		<pubDate>Thu, 07 Jul 2011 10:25:49 +0000</pubDate>
		<dc:creator>S4L</dc:creator>
				<category><![CDATA[teknik-teknik statistik]]></category>
		<category><![CDATA[cara uji item tes]]></category>
		<category><![CDATA[korelasi biserial]]></category>
		<category><![CDATA[korelasi pendidikan]]></category>
		<category><![CDATA[pengujian soal]]></category>
		<category><![CDATA[reliabilitas soal]]></category>
		<category><![CDATA[statistik pendidikan]]></category>

		<guid isPermaLink="false">http://ariyoso.wordpress.com/?p=884</guid>
		<description><![CDATA[Sehubungan dengan banyaknya permintaan bahasan mengenai korelasi biserial, maka akan diulas sedikit di Statistik 4 Life berikut ini. Korelasi biserial merupakan alat yang paling sering digunakan dalam dunia pendidikan, dimana korelasi ini melihat hubungan antara skor atau hasil jawaban pada masing-masing item pertanyaan yang diberikan dalam tes. Korelasi biserial efektif diberikan pada tipe tes multiple <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=ariyoso.wordpress.com&amp;blog=3010910&amp;post=884&amp;subd=ariyoso&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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			<media:title type="html">biserial_manual7</media:title>
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			<media:title type="html">biserial_manual_hasil pvalue</media:title>
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		<title>Model Autoregresif (AR)</title>
		<link>http://ariyoso.wordpress.com/2011/06/28/model-autoregresif-ar/</link>
		<comments>http://ariyoso.wordpress.com/2011/06/28/model-autoregresif-ar/#comments</comments>
		<pubDate>Tue, 28 Jun 2011 14:17:40 +0000</pubDate>
		<dc:creator>S4L</dc:creator>
				<category><![CDATA[ekonometrika]]></category>
		<category><![CDATA[autokorelasi parsial]]></category>
		<category><![CDATA[autoregresi]]></category>
		<category><![CDATA[data lag]]></category>
		<category><![CDATA[model autoregresi]]></category>
		<category><![CDATA[model autoregresif]]></category>
		<category><![CDATA[regresi linier dengan lag]]></category>
		<category><![CDATA[regresi metode lag]]></category>

		<guid isPermaLink="false">http://ariyoso.wordpress.com/?p=865</guid>
		<description><![CDATA[Kita hidup dalam dunia yang selalu berputar, dan waktu yang kita lewati setiap hari tanpa kita sadari ga akan bisa terulang kembali. Tukang sayur, tukang somay, pemain saham, pemerintah, wiraswasta, maupun para peneliti selalu berlomba dengan waktu untuk mengejar makna dalam hidup (ini mau bahas apa ya??soal hidup dan waktu melulu…heheheh), kita mau bahas time <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=ariyoso.wordpress.com&amp;blog=3010910&amp;post=865&amp;subd=ariyoso&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
		<wfw:commentRss>http://ariyoso.wordpress.com/2011/06/28/model-autoregresif-ar/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
	
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			<media:title type="html">AR-tabel</media:title>
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			<media:title type="html">AR-DW</media:title>
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			<media:title type="html">AR-hasil regresi</media:title>
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			<media:title type="html">AR-plot regresi linier</media:title>
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			<media:title type="html">AR-data residual</media:title>
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			<media:title type="html">AR-uji autokorelasi_1</media:title>
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		<media:content url="http://ariyoso.files.wordpress.com/2011/06/ar-uji-autokorelasi_2.jpg" medium="image">
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			<media:title type="html">AR-grafik autokorelasi</media:title>
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			<media:title type="html">AR-ilustrasi AR</media:title>
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			<media:title type="html">AR-langkah lag_1</media:title>
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			<media:title type="html">AR-langkah lag_3</media:title>
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			<media:title type="html">AR-output autoregresif_1</media:title>
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		<item>
		<title>Cross Tabulation (Crosstab)</title>
		<link>http://ariyoso.wordpress.com/2011/06/27/cross-tabulation-crosstab/</link>
		<comments>http://ariyoso.wordpress.com/2011/06/27/cross-tabulation-crosstab/#comments</comments>
		<pubDate>Mon, 27 Jun 2011 10:41:55 +0000</pubDate>
		<dc:creator>S4L</dc:creator>
				<category><![CDATA[teknik-teknik statistik]]></category>
		<category><![CDATA[crosstab]]></category>
		<category><![CDATA[data silang]]></category>
		<category><![CDATA[data tabulasi]]></category>
		<category><![CDATA[tabulasi silang]]></category>

		<guid isPermaLink="false">http://ariyoso.wordpress.com/?p=851</guid>
		<description><![CDATA[Dalam penelitian sosial ekonomi, kita akan seringkali menemukan data kategorik daripada data interval. Data ini biasanya dapat disajikan dalam 2 bentuk, dalam bentuk list atau table. Jika kita ingin melihat hubungan antara pekerjaan yang terdiri dari karyawan swasta (0), pegawai negeri (1), usaha sendiri (2) terhadap jenis kelamin (0=pria; 1=wanita) di sebuah kota “Y”, maka <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=ariyoso.wordpress.com&amp;blog=3010910&amp;post=851&amp;subd=ariyoso&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
		<wfw:commentRss>http://ariyoso.wordpress.com/2011/06/27/cross-tabulation-crosstab/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
	
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			<media:title type="html">crosstab_1</media:title>
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			<media:title type="html">crosstab_2</media:title>
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		<media:content url="http://ariyoso.files.wordpress.com/2011/06/crosstab_output.jpg" medium="image">
			<media:title type="html">crosstab_output</media:title>
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		<item>
		<title>Model Holt-Winters</title>
		<link>http://ariyoso.wordpress.com/2010/10/20/model-holt-winters/</link>
		<comments>http://ariyoso.wordpress.com/2010/10/20/model-holt-winters/#comments</comments>
		<pubDate>Wed, 20 Oct 2010 13:03:23 +0000</pubDate>
		<dc:creator>S4L</dc:creator>
				<category><![CDATA[ekonometrika]]></category>
		<category><![CDATA[additive]]></category>
		<category><![CDATA[holt]]></category>
		<category><![CDATA[model holt]]></category>
		<category><![CDATA[multiplicative]]></category>
		<category><![CDATA[peramalan bisnis]]></category>
		<category><![CDATA[winters]]></category>
		<category><![CDATA[winters multiplicative]]></category>

		<guid isPermaLink="false">http://ariyoso.wordpress.com/?p=827</guid>
		<description><![CDATA[Seringkali data time series menunjukkan gejala musiman. Musiman mengacu pada kecenderungan data time series menunjukkan gejala berulang pada setiap periode waktu tertentu atau pada setiap periode T. Sebagai contoh, harga daging sapi akan melonjak tinggi pada musim lebaran, atau harga cabe akan membumbung tinggi setiap bulan Desember. Pola ini akan terus berulang setiap tahunnya. Akan <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=ariyoso.wordpress.com&amp;blog=3010910&amp;post=827&amp;subd=ariyoso&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
		<wfw:commentRss>http://ariyoso.wordpress.com/2010/10/20/model-holt-winters/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
	
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			<media:title type="html">ariyoso</media:title>
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			<media:title type="html">HOLT_1</media:title>
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			<media:title type="html">holt_2</media:title>
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			<media:title type="html">HOLT_3</media:title>
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			<media:title type="html">HOLT_4</media:title>
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		<item>
		<title>Multidimensional Scaling</title>
		<link>http://ariyoso.wordpress.com/2010/01/26/multidimensional-scaling-mds/</link>
		<comments>http://ariyoso.wordpress.com/2010/01/26/multidimensional-scaling-mds/#comments</comments>
		<pubDate>Tue, 26 Jan 2010 16:47:03 +0000</pubDate>
		<dc:creator>S4L</dc:creator>
				<category><![CDATA[behaviourmetrika]]></category>
		<category><![CDATA[metode kuantitatif manajemen]]></category>
		<category><![CDATA[analisis MDS]]></category>
		<category><![CDATA[konsep multidimensional scaling]]></category>
		<category><![CDATA[multidimensional scaling]]></category>
		<category><![CDATA[pemetaan MDS]]></category>
		<category><![CDATA[pemetaan perseptual]]></category>
		<category><![CDATA[perceptual map]]></category>

		<guid isPermaLink="false">http://ariyoso.wordpress.com/?p=796</guid>
		<description><![CDATA[Tujuan dari multidimensional scaling (MDS) adalah untuk memberikan gambaran visual dari pola kedekatan yang berupa kesamaan atau jarak diantara sekumpulan objek-objek. Penerapan MDS dapat dijumpai pada visualisasi ilmiah dan data mining dalam ilmu kognitif, informasi, pemasaran maupun ekologi. Misalnya ketika konsumen  potensial diminta untuk membandingkan produk dan melakukan penilaian mengenai kesamaan produk tersebut. MDS dapat <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=ariyoso.wordpress.com&amp;blog=3010910&amp;post=796&amp;subd=ariyoso&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
		<wfw:commentRss>http://ariyoso.wordpress.com/2010/01/26/multidimensional-scaling-mds/feed/</wfw:commentRss>
		<slash:comments>17</slash:comments>
	
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			<media:title type="html">mds_3</media:title>
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			<media:title type="html">mds_4</media:title>
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			<media:title type="html">mds_5</media:title>
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			<media:title type="html">mds_6</media:title>
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		<item>
		<title>Regresi Data Panel</title>
		<link>http://ariyoso.wordpress.com/2010/01/17/regresi-data-panel/</link>
		<comments>http://ariyoso.wordpress.com/2010/01/17/regresi-data-panel/#comments</comments>
		<pubDate>Sun, 17 Jan 2010 11:35:18 +0000</pubDate>
		<dc:creator>S4L</dc:creator>
				<category><![CDATA[ekonometrika]]></category>
		<category><![CDATA[analisis data panel]]></category>
		<category><![CDATA[estimasi data panel]]></category>
		<category><![CDATA[prosedur regresi data panel]]></category>
		<category><![CDATA[regresi data panel]]></category>
		<category><![CDATA[tahap regresi data panel dengan eviews]]></category>

		<guid isPermaLink="false">http://ariyoso.wordpress.com/?p=787</guid>
		<description><![CDATA[Meneruskan bahasan sebelumnya mengenai pengantar data panel dan cara input data panel, maka pada bahasan ini akan ditunjukkan langkah-langkah melakukan regresi data panel dengan ilustrasi contoh yang cukup sederhana menggunakan bantuan eviews 5.1. Jika anda belum terlalu memahami apa itu data panel dan apa fungsinya anda bisa melihat terlebih dahulu pada bahasan sebelumnya disini &#62;&#62;&#62; <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=ariyoso.wordpress.com&amp;blog=3010910&amp;post=787&amp;subd=ariyoso&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
		<wfw:commentRss>http://ariyoso.wordpress.com/2010/01/17/regresi-data-panel/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
	
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			<media:title type="html">data panel reg_4</media:title>
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			<media:title type="html">data panel reg_5</media:title>
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		<title>MANOVA</title>
		<link>http://ariyoso.wordpress.com/2009/12/29/manova/</link>
		<comments>http://ariyoso.wordpress.com/2009/12/29/manova/#comments</comments>
		<pubDate>Tue, 29 Dec 2009 07:06:33 +0000</pubDate>
		<dc:creator>S4L</dc:creator>
				<category><![CDATA[teknik-teknik statistik]]></category>
		<category><![CDATA[uji-uji statistik]]></category>
		<category><![CDATA[manova]]></category>
		<category><![CDATA[manova dengan SPSS]]></category>
		<category><![CDATA[multivariat anova]]></category>
		<category><![CDATA[prosedur uji manova]]></category>

		<guid isPermaLink="false">http://ariyoso.wordpress.com/?p=782</guid>
		<description><![CDATA[Multiple analysis of variance (MANOVA) digunakan untuk melihat efek utama dan efek interaksi variabel kategorik pada variabel dependen interval. MANOVA menggunakan satu atau lebih variabel independen kategorik sebagai prediktor, seperti halnya ANOVA, tetapi MANOVA menggunakan lebih dari satu variabel dependen. Uji ANOVA menguji perbedaan mean pada variabel dependen untuk beberapa variabel independen, sedangkan MANOVA menguji <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=ariyoso.wordpress.com&amp;blog=3010910&amp;post=782&amp;subd=ariyoso&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
		<wfw:commentRss>http://ariyoso.wordpress.com/2009/12/29/manova/feed/</wfw:commentRss>
		<slash:comments>4</slash:comments>
	
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			<media:title type="html">ariyoso</media:title>
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		<title>Model Seemingly Unrelated Regression (SUR)</title>
		<link>http://ariyoso.wordpress.com/2009/12/28/seemingly-unrelated-regression/</link>
		<comments>http://ariyoso.wordpress.com/2009/12/28/seemingly-unrelated-regression/#comments</comments>
		<pubDate>Mon, 28 Dec 2009 15:46:47 +0000</pubDate>
		<dc:creator>S4L</dc:creator>
				<category><![CDATA[ekonometrika]]></category>
		<category><![CDATA[teknik regresi]]></category>
		<category><![CDATA[konsep regresi SUR]]></category>
		<category><![CDATA[model SUR]]></category>
		<category><![CDATA[Regresi SUR]]></category>
		<category><![CDATA[SUR dengan Eviews]]></category>

		<guid isPermaLink="false">http://ariyoso.wordpress.com/?p=775</guid>
		<description><![CDATA[Model seemingly unrelated regressions (SUR) diperkenalkan oleh Zellner pada tahun 1962, yang merupakan bahasan dari model regresi multivariat (multiple regression), dan merupakan bagian dari regresi linier. Model SUR terdiri atas beberapa sistem persamaan yang tidak berhubungan (unrelated). Artinya setiap variabel (dependen maupun independen) terdapat dalam satu sistem. Pada model SUR, error dari sistem yang berbeda <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=ariyoso.wordpress.com&amp;blog=3010910&amp;post=775&amp;subd=ariyoso&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
		<wfw:commentRss>http://ariyoso.wordpress.com/2009/12/28/seemingly-unrelated-regression/feed/</wfw:commentRss>
		<slash:comments>3</slash:comments>
	
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			<media:title type="html">SUR_1</media:title>
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		<title>Uji Heteroskedastisitas</title>
		<link>http://ariyoso.wordpress.com/2009/12/23/uji-heteroskedastisitas/</link>
		<comments>http://ariyoso.wordpress.com/2009/12/23/uji-heteroskedastisitas/#comments</comments>
		<pubDate>Wed, 23 Dec 2009 18:43:07 +0000</pubDate>
		<dc:creator>S4L</dc:creator>
				<category><![CDATA[teknik regresi]]></category>
		<category><![CDATA[homoskedastisitas]]></category>
		<category><![CDATA[masalah dalam regresi]]></category>
		<category><![CDATA[residual error]]></category>
		<category><![CDATA[uji glejser]]></category>
		<category><![CDATA[uji heteroskedastisitas]]></category>
		<category><![CDATA[uji white]]></category>

		<guid isPermaLink="false">http://ariyoso.wordpress.com/?p=766</guid>
		<description><![CDATA[Pada analisis regresi, heteroskedastisitas berarti situasi dimana keragaman variabel independen bervariasi pada data yang kita miliki. Salah satu asumsi kunci pada metode regresi biasa adalah bahwa error memiliki keragaman yang sama pada tiap-tiap sampelnya. Asumsi inilah yang disebut homoskedastisitas. Jika keragaman residual/error tidak bersifat konstan, data dapat dikatakan bersifat heteroskedastisitas. Karena pada metode regresi ordinary <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=ariyoso.wordpress.com&amp;blog=3010910&amp;post=766&amp;subd=ariyoso&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
		<wfw:commentRss>http://ariyoso.wordpress.com/2009/12/23/uji-heteroskedastisitas/feed/</wfw:commentRss>
		<slash:comments>16</slash:comments>
	
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			<media:title type="html">hetero_1</media:title>
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		<title>Regresi Dengan Eviews</title>
		<link>http://ariyoso.wordpress.com/2009/12/19/regresi-linier-dengan-eviews/</link>
		<comments>http://ariyoso.wordpress.com/2009/12/19/regresi-linier-dengan-eviews/#comments</comments>
		<pubDate>Sat, 19 Dec 2009 19:56:03 +0000</pubDate>
		<dc:creator>S4L</dc:creator>
				<category><![CDATA[teknik regresi]]></category>
		<category><![CDATA[contoh regresi linier berganda]]></category>
		<category><![CDATA[prosedur regresi linier berganda]]></category>
		<category><![CDATA[regresi linier berganda]]></category>
		<category><![CDATA[regresi linier dengan eviews]]></category>

		<guid isPermaLink="false">http://ariyoso.wordpress.com/?p=738</guid>
		<description><![CDATA[Meneruskan bahasan Regresi Linier Berganda sebelumnya, pada bahasan ini kita akan menjalankan regresi linier berganda dengan bantuan software eviews 5.1. Ilustrasi contoh: Seandainya kita memiliki variabel dependen (Y) tingkat inflasi di Amerika Serikat, dengan variabel independen yang diamati adalah kurs Yen terhadap US$ (X1), kurs Rupiah terhadap US$ (X2), dan kurs US$ terhadap Poundsterling (X3), <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=ariyoso.wordpress.com&amp;blog=3010910&amp;post=738&amp;subd=ariyoso&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
		<wfw:commentRss>http://ariyoso.wordpress.com/2009/12/19/regresi-linier-dengan-eviews/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
	
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