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Elements of Statistical Inference

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Mind Map on Elements of Statistical Inference, created by Paul Martín Sanc on 15/09/2015.
Paul Martín Sanc
Mind Map by Paul Martín Sanc, updated more than 1 year ago
Paul Martín Sanc
Created by Paul Martín Sanc about 10 years ago
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Elements of Statistical Inference
  1. Population and Sample
    1. Representative Sample
      1. Without Bias (Sesgo)
      2. Types of Sampling
        1. Simple
          1. Stratified
            1. Systematic
              1. Cluster
              2. Aleatory
                1. It can be modeling
                  1. Describe
                    1. Limit (acotar)
                  2. Finite
                    1. Infinite
                      1. Continuous Production
                        1. The process flow does not stop
                          1. Extract some products in one point of the process in order to make quality control
                        2. Mass Production
                      2. Statistical Parameters
                        1. We use them to estimate statistical parameters of population
                          1. Mean (µ)^
                            1. Standard deviation (S)^
                              1. Proportion of defects (p)^ in %
                              2. The symbol ^ is just to represent that comes from sample and not population
                              3. Probability Distribution
                                1. Normal
                                  1. t Student
                                    1. chi-quarter
                                      1. F distriution
                                      2. Estimation
                                        1. Punctual
                                          1. We use Statistical Parameters
                                            1. If variation between two punctual estimation is high
                                              1. How close of parameters of population is my punctual estimation?
                                                1. Use Standard Error
                                                  1. If we want a specific error
                                                    1. Estimate Sample Size
                                            2. By Intervals
                                              1. Do before Descriptive Analysis of Data
                                                1. Confidence Interval
                                                  1. The amplitud of this depends on:
                                                    1. Size of the sample
                                                      1. Population
                                                        1. Variance
                                                          1. Level of confidence
                                                        2. Mean (µ)^
                                                          1. Proportion of defects (p)^ in %
                                                            1. Normal distribution supported by binomal distribution
                                                              1. n*p ≥ 5 and n*(1 − p) ≥ 5.
                                                            2. Variance
                                                      2. Hypothesis Testing
                                                        1. Null Hypothesis
                                                          1. Statistical Test
                                                            1. Unilateral Hypothesis
                                                              1. Bilateral Hyptohesis
                                                              2. Rejection Criteria
                                                                1. Alternative Hypothesis

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