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b:head_first_statistics:constructing_confidence_intervals [2019/12/09 08:54] – [Four steps for finding confidence intervals] hkimscilb:head_first_statistics:constructing_confidence_intervals [2023/11/15 08:24] (current) – [Four steps for finding confidence intervals] hkimscil
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 Rather than specify an exact value, we can specify two values we expect flavor duration to lie between.  Rather than specify an exact value, we can specify two values we expect flavor duration to lie between. 
  
-[{{:b:head_first_statistics:pasted:20191203-121916.png  }}] : As an example, you may want to choose a and b so that there’s a 95% chance of the interval containing the population mean. Finding the exact spot of a and b is the problem we are trying to solve.+<WRAP group> 
 +<WRAP 25% column> 
 +$\Large{P(a < \mu < b) = 0.95$   
 +</WRAP> 
 +<WRAP 50% column> 
 +As an example, you may want to choose a and b so that there’s a 95% chance of the interval containing the population mean. Finding the exact spot of a and b is the problem we are trying to solve.  
 +</WRAP> 
 +</WRAP>
  
 The far side of each end, (a, b) is called a **//confidence interval//**. The far side of each end, (a, b) is called a **//confidence interval//**.
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 {{:b:head_first_statistics:pasted:20191203-123432.png}} {{:b:head_first_statistics:pasted:20191203-123432.png}}
-<WRAP box>+
 $$P(z_{a} < Z < z_{b}) = 0.95$$ $$P(z_{a} < Z < z_{b}) = 0.95$$
 $$P(Z < z_{a}) = 0.025$$ $$P(Z < z_{a}) = 0.025$$
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 $(61.72, 63.68)$ 을 전체 population의 단맛의 지속시간으로 삼는다.  $(61.72, 63.68)$ 을 전체 population의 단맛의 지속시간으로 삼는다. 
 +
 +
 +<WRAP box>
 +위의 1.96이 이해하고자 하는 것을 어렵게 하는 경향이 있음. 
 +
 +  * 강사의 초기 강의 중에서 표준편차의 특성 중에서 68, 95, 99%에 대한 것으로 대체해서 생각하면
 +  * 표준점수로 했을 때 +- SD 1, 2, 3 에 해당되는 probability이 (면적) 각각 68, 95, 99%
 +  * 따라서 위의 경우는 95%에 해당하는 probability는 
 +    * $P(-2 < z < 2) = .95$
 +    * $P(-2 < \dfrac {\overline{X} - \mu}{sd} < 2) = .95$
 +    * 이렇게 계산을 하면
 +    * $P(\overline{X} -1 < \mu < \overline{X} + 1) = .95 $
 </WRAP> </WRAP>
  
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 {{:b:head_first_statistics:pasted:20191203-133241.png}} {{:b:head_first_statistics:pasted:20191203-133241.png}}
-v is called the **<fc #ff0000><fs large>number of degrees of freedom</fs></fc>**+ 
 +v is called the number of **<fc #ff0000><fs large>degrees of freedom</fs></fc>**
  
 {{:b:head_first_statistics:pasted:20191203-133508.png}} {{:b:head_first_statistics:pasted:20191203-133508.png}}
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 ==== Step 4: Find the confidence limits ==== ==== Step 4: Find the confidence limits ====
 {{:b:head_first_statistics:pasted:20191203-133742.png}} {{:b:head_first_statistics:pasted:20191203-133742.png}}
 +Use degrees of freedom with alpha (p-level)
  
 ===== The t-distribution vs. the normal distribution ===== ===== The t-distribution vs. the normal distribution =====
 {{:b:head_first_statistics:pasted:20191203-133845.png}} {{:b:head_first_statistics:pasted:20191203-133845.png}}
 +
 +===== Exercise =====
 +<WRAP help>
 +Mighty Gumball has noticed a problem with their gumball dispensers. They have taken a sample of 30 machines, and found that the mean number of malfunctions is 15. Construct a 99% confidence interval for the number of malfunctions per month.
 +</WRAP>
 +
 +위는 Poisson distribution이므로 $X \sim Po(15)$ 이고 $E(X) = \lambda$이고 $Var(X) = \lambda$이다. 따라서
 +
 +$$\text {confidence interval} = (\overline{X} - c * se, \;\; \overline{X} + c * se)$$
 +$$\text{se} = \sqrt{(15/30)}$$ 이고
 +$$\text{c} = 2.58 (3) $$ 이므로
 +
 +\begin{eqnarray*}
 +\text {confidence interval} & = & (\overline{X} - c * se, \;\; \overline{X} + c * se) \\
 +& = & (15 - 3 * \sqrt{(15/30)}, \;\; 15 + 3 * \sqrt{(15/30)}) \\
 +& = & (15 - 2.58 * \sqrt{(15/30)}, \;\; 15 + 2.58 * \sqrt{(15/30)}) \\
 +& = & (15 - 2.58 * 0.707, \;\; 15 + 2.58 * 0.707) \\
 +& = & (15 - 1.824, \;\; 15 + 1.824) \\
 +& = & (13.176, \;\; 16.824) 
 +\end{eqnarray*}
b/head_first_statistics/constructing_confidence_intervals.1575849269.txt.gz · Last modified: 2019/12/09 08:54 by hkimscil

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