| Confidence Estimation  
                
                  | Topic Review on "Title": |  
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                                  Confidence  Interval (CI) for a population parameter is:An  interval between two numbers with an associated probability p which is generated from a random  sample of an underlying population,
 Such  that if the sampling was repeated numerous times and the confidence interval  recalculated from each sample according to the same method,
 A  proportion p of the confidence  intervals would contain the population parameter in question. Take an SRS of  size n from a large population that  contains a proportion parameter p of  successes.
 Let  π be the sample proportion of successes.  If the sample is large enough, then.
                                      The  sampling distribution of π is approximately normal.
 
  The mean of the sampling distribution  is p.
 The  standard deviation of the sampling distribution is:
 Formula  for CIzα/2 is called the critical value of the normal  distribution at α level.
 A  table on next slide will gives you zα/2  for a particular level of confidence
  
 
                                    
                                      | Commonly used values    of za/2 |  
                                      | Confidence level |   |   |  
                                      | 100(1-a) | a | a/2 | za/2 |  
                                      | 90% | .10 | .05 | 1.65 |  
                                      | 95% | .05 | .025 | 1.96 |  
                                      | 99% | .01 | .005 | 2.58 |  CI for  t-distribution Small  sample size population means
 When  creating a Confidence interval around m for a small sample we use (the df for ta/2  is n-1)
  
 Assumption: random sample and population is approximately  normally distributed
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                  | Rapid Study Kit for "Title": |  
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                  | "Title" Tutorial Summary : |  
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                                  This tutorial shows the principal concepts of confidence  estimation. In statistics, interval estimation is the use of sample data to calculate  an interval of possible (or probable) values of an unknown population  parameter. The most prevalent  forms of interval estimation are confidence  intervals.
 By completing this course, you will learn about the confidence estimation, including confidence  intervals, confidence intervals  for population proportions, confidence  intervals for the difference between two population proportions, confidence interval for population  means, confidence intervals for  the difference between two population means and small sample size confidence interval for population means |  
 
                
                  | Tutorial Features: |  
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                                  Specific  Tutorial Features: 
                                    Several  example problems with step by step illustrations of calculating confidence  intervals are presented.
Confidence  intervals for the difference between two population proportions, and two population means are given for  detailed explanation on how to  calculate confidence intervals. Series  Features: 
                                    Concept  map showing inter-connections of new concepts in this tutorial and those  previously introduced.
Definition  slides introduce terms as they are needed.
Visual  representation of concepts
Animated  examples—worked out step by step
A  concise summary is given at the conclusion of the tutorial. |  
 
                
                  | "Title" Topic List: |  
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                                      Confidence  Intervals
Confidence  Intervals for population proportions
Confidence  Intervals for the difference between two population proportions
Confidence  Interval for population means
Confidence  Intervals for the difference between two population means
Small  Sample Size Confidence Interval for population means |  
 
 See all 24 lessons in Introductory Statistics, including concept tutorials, problem drills and cheat sheets:Teach Yourself Introductory Statistics Visually in 24 Hours
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