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  1. New View of Statistics: P Values - Sportsci


    P Values and Confidence Intervals Speaking of confidence intervals, let's bring them back into the picture.It's possible to show that the two definitions of statistical significance are compatible--that getting a p value of less than 0.05 is the same as having a 95% confidence interval that doesn't overlap zero.I won't try to explain it, other than to say that you have to slide the confidence ...

  2. p-value - Wikipedia


    In statistical hypothesis testing, the p-value or probability value or asymptotic significance is the probability for a given statistical model that, when the null hypothesis is true, the statistical summary (such as the sample mean difference between two compared groups) would be greater than or equal to the actual observed results. The use of p-values in statistical hypothesis testing is ...

  3. Confidence/prediction intervals | Real Statistics Using Excel


    The 95% confidence interval for the forecasted valuesof x is. where. This means that there is a 95% probability that the true linear regression line of the population will lie within the confidence interval of the regression line calculated from the sample data.

  4. Calculator for confidence intervals for odds ratio ...


    Odds ratio OR = 95% confidence interval = A permanent record of the analysis can be obtained by printing the page. Odds ratio calculator - select your own confidence interval

  5. A beginner’s guide to interpreting odds ratios, confidence ...


    Confidence interval (CI) The confidence interval indicates the level of uncertainty around the measure of effect (precision of the effect estimate) which in this case is expressed as an OR.

  6. One- and two-tailed tests - Wikipedia


    In coin flipping, the null hypothesis is a sequence of Bernoulli trials with probability 0.5, yielding a random variable X which is 1 for heads and 0 for tails, and a common test statistic is the sample mean (of the number of heads) ¯. If testing for whether the coin is biased towards heads, a one-tailed test would be used – only large numbers of heads would be significant.

  7. Hypothesis Testing for Means & Proportions


    This is the first of three modules that will addresses the second area of statistical inference, which is hypothesis testing, in which a specific statement or hypothesis is generated about a population parameter, and sample statistics are used to assess the likelihood that the hypothesis is true.

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