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        <dc:creator>hkimscil (hkimscil@undisclosed.example.com)</dc:creator>
        <title>t-test_summary - [ro.hypothesis.testing] </title>
        <link>http://commres.net/t-test_summary?rev=1775975881&amp;do=diff</link>
        <description>t-test sum up


rm(list=ls())
rnorm2 &lt;- function(n,mean,sd){ mean+sd*scale(rnorm(n)) }
ss &lt;- function(x) { sum((x-mean(x))^2) }
z.test &lt;- function(sam, mu, sigma) {
  diff &lt;-mean(sam) - mu
  se &lt;- sigma / sqrt(length(sam))
  z.cal &lt;- diff / se
  p.val &lt;- pnorm(abs(z.cal), lower.tail = F)*2
  two &lt;- abs(qnorm(.05/2))
  return(cat(
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  …</description>
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        <dc:creator>hkimscil (hkimscil@undisclosed.example.com)</dc:creator>
        <title>schedule - [Week 7] </title>
        <link>http://commres.net/c/mrm/2026/schedule?rev=1775967420&amp;do=diff</link>
        <description>이전 페이지

---- exploring media theories

	*  Week 01: March 2, 5
	*  Week 02: March 9, 12
	*  Week 03: March 16, 19
	*  Week 04: March 23, 26 (the 1st quiz)

---- choosing media theories

	*  Week 05: March 30, April 2 
	*  Week 06: April 6, 9 

---- developing and revising hypotheses</description>
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        <title>two_sample_t-test - [ro.two.sample.t-test] </title>
        <link>http://commres.net/r/two_sample_t-test?rev=1775602951&amp;do=diff</link>
        <description>Independent sample t-test 의 standard error 값을 구하는 방법이 얼른 머리에 들어오지 않으면, 
see mean and variance of the sample mean: 샘플평균들의 집합이 가지는 평균과 분산 (CLT)
sa statistical review: 분산의 계산

두 샘플을 취해서 평균을 구한 후 (mean of A, mean of B), 그 차이를 기록하는 것을 무한히 하여 그 분포를 구하는 것은 아래와 같이 정리, 이해할 수 있다. 
\begin{eqnarray}
E \left[ \overline{X} - \overline{Y} \right] &amp; = &amp; E \left[ \overline{X} \right] - E \left[ \overline{Y} \right]
&amp; = &amp; {\mu_{X}} - {\mu_{Y}} \\
V \left[ \overline{X} - \overline{Y} \right] &amp; = &amp; V \left[ \overli…</description>
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        <dc:date>2026-04-07T23:00:52+00:00</dc:date>
        <dc:creator>hkimscil (hkimscil@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>2026-04-07T22:39:53+00:00</dc:date>
        <dc:creator>hkimscil (hkimscil@undisclosed.example.com)</dc:creator>
        <title>two_sample_t-test</title>
        <link>http://commres.net/two_sample_t-test?rev=1775601593&amp;do=diff</link>
        <description>Two sample t-test

Independent sample t-test, two sample t-test 
Difference of Two means Hypothesis test 등 같은 의미

Theory

가정

	*  두 모집단 p1, p2 가 있다
	*  각 집단에서 샘플을 취해서 그 평균을 구한 후
	*  그 차이를 기록한다. \begin{eqnarray*}
\overline{X} &amp; \sim &amp; \left( \mu, \;\; \frac{\sigma^2}{n} \right) \\
&amp;  &amp; \text{in other words, } \\
E \left[ \overline{X} \right] &amp; = &amp; \mu \\
Var \left[ \overline{X} \right] &amp; = &amp; \frac{\sigma^2}{n} \\
&amp; &amp; \text {Assuming that X1 and X2 are independent } \\
\overline{X_{1}} &amp; \sim &amp; \l…</description>
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        <dc:date>2026-04-07T22:30:39+00:00</dc:date>
        <dc:creator>hkimscil (hkimscil@undisclosed.example.com)</dc:creator>
        <title>mean_and_variance_of_the_sample_mean</title>
        <link>http://commres.net/mean_and_variance_of_the_sample_mean?rev=1775601039&amp;do=diff</link>
        <description>Mean and variance of sample mean

전제: Expected value (기대값)와 Variance (분산)의 연산에 과한 법칙으로는  참조.

X,Y are Independent variables.

\begin{eqnarray*}
E[aX] &amp;=&amp; a E[X] \\
E[X+Y] &amp;=&amp; E[X] + E[Y] \\
Var[aX] &amp;=&amp; a^{\tiny{2}} Var[X] \\
Var[X+Y] &amp;=&amp; Var[X] + Var[Y]  \\
Var[X-Y] &amp;=&amp; Var[X] + Var[Y]  
\end{eqnarray*}

Mean of the sample mean

평균이 (mean) $\mu$ 이고, 분산이 (variance) $\sigma^{2}$ 인 모집단에서 (population) 독립적으로 추출되어 관찰되는 $X_{1}, X_{2}, . . . , X_{n}$$X_1$\begin{eqnarray*}
X_{1}, X_{2}, X_{3}, . . . , X_…</description>
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        <dc:creator>hkimscil (hkimscil@undisclosed.example.com)</dc:creator>
        <title>schedule - [Week07] </title>
        <link>http://commres.net/c/ms/2026/schedule?rev=1775487210&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:creator>hkimscil (hkimscil@undisclosed.example.com)</dc:creator>
        <title>week06_t-test_and_anova_note - created</title>
        <link>http://commres.net/c/ms/2026/schedule/week06_t-test_and_anova_note?rev=1775483140&amp;do=diff</link>
        <description>see anova note</description>
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        <dc:creator>hkimscil (hkimscil@undisclosed.example.com)</dc:creator>
        <title>building_hypotheses</title>
        <link>http://commres.net/c/mrm/2026/schedule/building_hypotheses?rev=1775445233&amp;do=diff</link>
        <description>Research Idea:

	*  How relating other influencers affect users&#039; experiences?
		*  search results

	*  How relating other influencers affect users&#039; experience of youtube viewing
		*  search results

	*  watching influencers&#039; content and users&#039; behavior change
		*  search results
		*  The effect of social media influencers&#039; on teenagers Behavior: an empirical study using cognitive map technique
			*  not a good example of building hypotheses</description>
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        <dc:date>2026-04-05T23:57:44+00:00</dc:date>
        <dc:creator>hkimscil (hkimscil@undisclosed.example.com)</dc:creator>
        <title>20260405-235744.png - created</title>
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        <description>&lt;img src=&quot;http://commres.net/_media/r/pasted/20260405-235744.png?w=500&amp;amp;h=500&amp;amp;tok=7358e9&quot; alt=&quot;20260405-235744.png&quot; loading=&quot;lazy&quot; width=&quot;500&quot; height=&quot;500&quot; /&gt;</description>
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        <dc:date>2026-04-05T23:57:33+00:00</dc:date>
        <dc:creator>hkimscil (hkimscil@undisclosed.example.com)</dc:creator>
        <title>20260405-235733.png - created</title>
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        <description>&lt;img src=&quot;http://commres.net/_media/r/pasted/20260405-235733.png?w=500&amp;amp;h=500&amp;amp;tok=5e1eed&quot; alt=&quot;20260405-235733.png&quot; loading=&quot;lazy&quot; width=&quot;500&quot; height=&quot;500&quot; /&gt;</description>
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