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picture1_Hypothesis Testing Ppt 68992 | 27 Statistical Significance Using Confidence Intervals(ug1434 35)a With Qs


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File: Hypothesis Testing Ppt 68992 | 27 Statistical Significance Using Confidence Intervals(ug1434 35)a With Qs
1 what is the value of level of significance 2 what is the inference for a i p value 0 05 3 what concepts will be used for hypothesis testing ...

icon picture PPTX Filetype Power Point PPTX | Posted on 29 Aug 2022 | 3 years ago
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       (1) What is the value of level of 
       significance ?
       (2) What  is the inference for a (i) p-
       value <= 0.05 and (ii) p-value >0.05
       (3) What concepts will be used for 
       hypothesis testing and estimation ?
       (4) What are the factors which affects 
       the width of confidence interval ?
       Estimation
   Two forms of estimation
    Point estimation =  single value, e.g., 
     (mean, proportion, difference of two 
     means, difference of two proportions, OR, 
     RR etc.,)
    Interval estimation =  range of values  
     confidence interval (CI). A confidence 
     interval consists of:
     Confidence intervals
   “Statistics means never having to say you’re certain!”
            P values give no indication about the clinical 
             importance of the observed association
            Relying on information from a sample will always 
             lead to some level of uncertainty.
            Confidence interval is a range of values that tries 
             to quantify this uncertainty:
               For example , 95% CI means that under 
                repeated sampling 95% of CIs would contain 
                the true population parameter                  4
     P-values versus Confidence intervals
          P-value answers the question...
             "Is there a statistically significant difference 
               between the two treatments?“ (or two groups)
          The point estimate and its confidence interval 
            answers the question...
             "What is the size of that treatment difference?", 
               and "How precisely did this trial determine or 
               estimate the treatment difference?"
                                                                  5
     Computing confidence intervals (CI)
           General formula:
              (Sample statistic)   [(confidence level)  (measure of how high 
             the sampling variability is)]
           Sample statistic: observed magnitude of effect or 
             association (e.g., odds ratio, risk ratio, single mean, single 
             proportion, difference in two means, difference in two 
             proportions, correlation, regression coefficient, etc.,)
           Confidence level: varies – 90%, 95%, 99%.  For 
             example, to construct a  95% CI, Z/2 =1.96
           Sampling variability: Standard error (S.E.) of the 
             estimate is a measure of variability
                                                                          6
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