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       <dc:date>2026-04-15T02:32:06+00:00</dc:date>
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    <item rdf:about="http://commres.net/c/ms/2026/lecture_note_week_04?rev=1774996088&amp;do=diff">
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        <dc:date>2026-03-31T22:28:08+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>lecture_note_week_04</title>
        <link>http://commres.net/c/ms/2026/lecture_note_week_04?rev=1774996088&amp;do=diff</link>
        <description>퀴즈 1 문제 중

모집단 Mean = 180; SD = 20, 정규분포일때

49. N=16의 샘플을 추출할 때 샘플들의 평균 분포가 갖는 표준편차 값은?
standard error 값을 묻는 질문이므로
se = sigma / sqrt(n) = 20 / 4 = 5

50. n=400일 때 샘플평균들의 분포가 갖는 표준편차 값은?
1</description>
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        <dc:format>text/html</dc:format>
        <dc:date>2026-04-07T23:00:52+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>lecture_note_week_05</title>
        <link>http://commres.net/c/ms/2026/lecture_note_week_05?rev=1775602852&amp;do=diff</link>
        <description>모집단의 평균과 표준편차를 알고 있을 때

독립변인의 효과를 알고 싶을 때, 혹은 모집단의 성격이 참인지 거짓인지 알고 싶을 때
One sample z-test
t-test 꼭 읽을 것
Distribution of Sample Means -- mu = 40, sigma = 4 (hence var = 16) 인 모집단에서 n = n 사이즈의 샘플링을 무한 반복할 때 그 샘플평균들이 모인 집합 $ \frac {\text{obtained difference}} {\text{se}} = \frac {\text{difference due to the IV}} {\text{random error}} $\begin{eqnarray}
z\;\;\;\text{or}\;\;\;t &amp; = &amp; \frac{\overline{X}-\mu}{\sigma_{\overline{X}} }, \quad \text{where } \;\; \sigma_{\overline{X}} = \frac{\sigma}{\sqrt{n…</description>
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        <dc:date>2026-04-15T00:44:49+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>normal_and_t_distribution_graph_comparison</title>
        <link>http://commres.net/c/ms/2026/normal_and_t_distribution_graph_comparison?rev=1776213889&amp;do=diff</link>
        <description># difference between normal(z) distribution and t distribution
curve(dnorm(x), from = -4, to = 3+4, 
      main = &quot;normalized distribution of sample means&quot;, 
      ylab = &quot;Density&quot;, xlab = &quot;z-value&quot;, col = &quot;black&quot;, lwd = 2)
curve(dt(x, 3), from = -4, to = 3+4, 
      main = &quot;normalized distribution of sample \n means from p1 and p2 (n=16)&quot;, 
      ylab = &quot;Density&quot;, xlab = &quot;z-value&quot;, col = &quot;red&quot;, lwd = 2, add=T)
curve(dt(x, 7), from = -4, to = 3+4, 
      main = &quot;normalized distribution of sample…</description>
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        <dc:format>text/html</dc:format>
        <dc:date>2026-04-14T23:40:52+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>schedule</title>
        <link>http://commres.net/c/ms/2026/schedule?rev=1776210052&amp;do=diff</link>
        <description>통계에 대한 기초적인 이해
가설과 가설검증

	*  가설의 종류와 그 종류에 따른 통계분석법
		*  z-test
		*  t-test
		*  ANOVA
		*  Factorial ANOVA
		*  correlation
		*  regression
		*  multiple regression
		*  factor analysis</description>
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        <dc:format>text/html</dc:format>
        <dc:date>2026-04-14T23:41:14+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>w07_factorial_anova_note</title>
        <link>http://commres.net/c/ms/2026/w07_factorial_anova_note?rev=1776210074&amp;do=diff</link>
        <description>see factorial anova
sa factorial anova</description>
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