# Any difference in the p value with p standing for

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Any difference in the p-value, with p standing for probability Compare p value to alpha The meaning of the p-value [NB] *If P is Low Ho must go* Downloaded by:: bryce0736 | [email protected] Distribution of this document is illegal

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Stuvia.com - The study-notes marketplace P value = significant level (sig) A p-value is the evidence against a null hypothesis. It does not tell you that the null hypothesis is correct or right, only if there is significant evidence to reject it or not. If the real truth was that the null hypotheses was true, what is the change that I will see a value or more extreme? If the p- value is small it means that the chance of me seeing such a value is small and can be confused for the Type I error. SO then it is impossible for the null hypotheses to be true. Misunderstandings about p -values The p -value is not… …the probability that the null hypothesis is true OR the probability that the alternative hypothesis is false. …the probability that a finding is "merely a fluke.” …the probability of falsely rejecting the null hypothesis. …the probability that replicating the experiment would yield the same conclusion. The significance level, such as 0.05, is not determined by the p - value. Rather, the significance level is decided by the person conducting the experiment before the data are viewed, and it is compared against the calculated p -value after the test has been performed. The p -value does not indicate the size or importance of the observed effect. Downloaded by:: bryce0736 | [email protected] Distribution of this document is illegal
Stuvia.com - The study-notes marketplace Hypothesis Test: Inferential Statistics: 1. Univariate statistical analysis – testing for ONE dependent variable 2. Bivariate statistical analysis – testing for TWO dependent variables 3. Multivariable statistical analysis – tests for THREE OR MORE dependent variables Input (X) Output (Y) Data Combinations and Tool Sets Output - Y Input - X Graphical Tool Statistical Tool Continuous Categorical Boxplots Graph>Boxplot Individual Value Plot Graph>Individual Value Plot Interval Plot Graph>Interval Plot (Location, Operator, Machine, Day of Week) (Cycle Time, Thickness, Weight, Volume) Means Std Dev 1 Sample t-test Stat>B.S.>1 Sample t 2 Sample t-test Stat>B.S.>1 Sample t 1 Variance Stat>B.S.>D.D.S 2 Variance Stat>B.S.>2 Variance To be used in conjunction with Hypothesis Roadmap Paired t Stat>B.S.>Paired t a - a b - b Inputs Levels/ Input 1 1 1 2 1 2 ANOVA Stat>ANOVA>One Way Multi Variance Stat>ANOVA>Test for Equal Variance 1 2+ 2 Way ANOVA Stat>ANOVA>Two Way 2 2+ Gnrl Linear Model Stat>ANOVA>GLM 2+ 2+ Assumptions Main Effects Plot Stat>ANOVA>Main Effects Plot Interaction Plot Stat>ANOVA>Interaction Plot Multi-Vari Chart Stat>Quality Tools>Multi Vari Chart Equal Variance between each level of input Normality for each level of input Stat>B.S.>Normality Test Use Variance Tests Shown Random Data Independance Downloaded by:: bryce0736 | [email protected] Distribution of this document is illegal

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Stuvia.com - The study-notes marketplace
• Fall '19
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