Difference between revisions of "SOCR EduMaterials Activities ConfidenceIntervals"

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(See also: added a link to general CI activity)
 
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== [[SOCR_EduMaterials_Activities | SOCR Educational Materials - Activities ]] - SOCR COnfidence Intervals Activity ==
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== [[SOCR_EduMaterials_Activities | SOCR Educational Materials - Activities ]] - SOCR Confidence Intervals Activity ==
  
== URL Go to: http://www.socr.ucla.edu/htmls/SOCR_Experiments.html ==
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Go to the [http://socr.ucla.edu/htmls/exp/Confidence_Interval_Experiment.html SOCR Confidence Interval applet]. Choose the '''Confidence Interval (CI) Experiment'''. In this [[Help_pages_for_SOCR_Experiments | experiment]] you will investigate the empirical properties of the sample-size, confidence level, the size of the constructed confidence interval and the practical utilization of Confidence Intervals in statistical data analysis
=== Choose the Confidence Interval Experiment. In this [Help_pages_for_SOCR_Experiments experiment] you will investigate the emperical properties of the sample-size, confidence level, the size of the constructed confidence interval and the practical utilization of Confidence Intervals in statistical data analysis ===
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<center>[[Image:SOCR_Activities_CI_Dinov_092206_Fig1.jpg|300px]]</center>
  
* Exercise 1: Consider a Poisson random variable X with parameter λ=1.5. Select the Poisson distribution in the applet, and r=1.5 (since r represents the parameter, λ). Then set n=1 to indicate that you have only one random variable.   Do not touch anything else. You will see a blue distribution on the right and on the left. The distribution on the left is the theoretical distribution of the X that we specified and the distribution on the right is the theoretical distribution of the sample average  (which in the applet is denoted by M).   Let's denote the sample average by <b>X<sup>-</sup></b>!
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===Exercise 1===
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Chose the confidence level (α), the sample-size and the number of experiments (see the image below). Click on the <nowiki><STEP></nowiki> button - this performs one set of experiments (20 in this case). Each experiment consist of generating a random sample of the given size (5, in this case) from the standard Normal Distribution, N(0,1). The samples along with the constructed confidence intervals are then displayed. Notice the experiments that have a green dot below the corresponding confidence intervals. These are the cases where the <i>parameter</i> being estimated by the confidence interval (population mean, in this case) is outside the corresponding confidence interval (above the right-CI-limit, or below the left-CI-limit).  
  
* Question 1(a): Compare these two theoretical distributions.  Attach a snapshot of how they look and the theoretical distribution tables below them. They are exactly the same! Because when n=1, X<sup>-</sup>=X.
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You can use the <nowiki><SHAPSHOT></nowiki> button to save as a JPEG image the state of your SOCR experiment on your local computer. The <nowiki><RUN></nowiki> allows you to sequantially run large number of sets of experiments (determined by the <nowiki><Number of Experiments></nowiki> selection) and monitor the results. Also, the text-area on the bottom of the applet summarizes the results of these experiments.
<center>[[Image:SOCR_Activities_CI_Dinov_092206_Fig1.jpg|300px]]</center>
 
  
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<center>[[Image:SOCR_Activities_CI_Dinov_092206_Fig2.jpg|300px]]</center>
 
   
 
   
* Question 1(b): Compare the Mean of the theoretical distribution of  the X variable and that of the Mean of the distribution of the   (the distribution of the M). These are theoretical means. What is their relation?
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====Question 1====
The Mean of the theoretical distribution of the X is 1.5, while that of the Mean of the distribution of the   is 1.5, too. They are the same. Theoretically, E(X<sup>-</sup>) = E(X) is always true if X<sup>-</sup> is the mean of several independent and identical random variables (IID) no matter how large is n.
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Would you get the same results (what are the results?) if you did this again? If someone else did this? Explain!
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===Exercise 2===
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Now change the sample-size (from 5 to 35) and press <nowiki><STEP></nowiki>, or <nowiki><RUN></nowiki>. You will notice that the result of the experiment changes significantly (e.g., we have 35 randomly sampled observations plotted in each of the 20 experiments). Also, observe the new summary statistics on the bottom.
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<center>[[Image:SOCR_Activities_CI_Dinov_092206_Fig3.jpg|300px]]</center>
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====Question 2====
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Does the fact that we increased (to 35) the sample-size caused the lack of green-dots (indicators of CIs that do not contain the estimated parameter, μ=0) on this outcome?
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How are the CI widths effected by this sample-size increase? Is there a theoretical reason for this observation? Explain! Are we more or less likely to get extreme observations now (sample-size=35) than before (when the sample-size=5)?
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===Exercise 3===Finally try changing the alpha-level (α) and the number of experiments? What effects can you predict?
  
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<center>[[Image:SOCR_Activities_CI_Dinov_092206_Fig4.jpg|300px]]</center>
  
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====Question 3====
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Do you expect an effect on the amount or frequency of the green-dots, when y ou alter the values for α and number of experiments?
  
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===See also===
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* [[SOCR_EduMaterials_Activities_CoinfidenceIntervalExperiment | Another SOCR Confidence Interval Activity]].
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* [[SOCR_EduMaterials_Activities_General_CI_Experiment | General SOCR Confidence Interval Activity]].
  
 
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Latest revision as of 01:03, 24 November 2009

SOCR Educational Materials - Activities - SOCR Confidence Intervals Activity

Go to the SOCR Confidence Interval applet. Choose the Confidence Interval (CI) Experiment. In this experiment you will investigate the empirical properties of the sample-size, confidence level, the size of the constructed confidence interval and the practical utilization of Confidence Intervals in statistical data analysis

SOCR Activities CI Dinov 092206 Fig1.jpg

Exercise 1

Chose the confidence level (α), the sample-size and the number of experiments (see the image below). Click on the <STEP> button - this performs one set of experiments (20 in this case). Each experiment consist of generating a random sample of the given size (5, in this case) from the standard Normal Distribution, N(0,1). The samples along with the constructed confidence intervals are then displayed. Notice the experiments that have a green dot below the corresponding confidence intervals. These are the cases where the parameter being estimated by the confidence interval (population mean, in this case) is outside the corresponding confidence interval (above the right-CI-limit, or below the left-CI-limit).

You can use the <SHAPSHOT> button to save as a JPEG image the state of your SOCR experiment on your local computer. The <RUN> allows you to sequantially run large number of sets of experiments (determined by the <Number of Experiments> selection) and monitor the results. Also, the text-area on the bottom of the applet summarizes the results of these experiments.

SOCR Activities CI Dinov 092206 Fig2.jpg

Question 1

Would you get the same results (what are the results?) if you did this again? If someone else did this? Explain!


Exercise 2

Now change the sample-size (from 5 to 35) and press <STEP>, or <RUN>. You will notice that the result of the experiment changes significantly (e.g., we have 35 randomly sampled observations plotted in each of the 20 experiments). Also, observe the new summary statistics on the bottom.

SOCR Activities CI Dinov 092206 Fig3.jpg

Question 2

Does the fact that we increased (to 35) the sample-size caused the lack of green-dots (indicators of CIs that do not contain the estimated parameter, μ=0) on this outcome? How are the CI widths effected by this sample-size increase? Is there a theoretical reason for this observation? Explain! Are we more or less likely to get extreme observations now (sample-size=35) than before (when the sample-size=5)?

===Exercise 3===Finally try changing the alpha-level (α) and the number of experiments? What effects can you predict?

SOCR Activities CI Dinov 092206 Fig4.jpg

Question 3

Do you expect an effect on the amount or frequency of the green-dots, when y ou alter the values for α and number of experiments?

See also




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