Any difference in the pvalue, with p standing for probability
Compare p value to alpha
The meaning of the pvalue [NB]
*If P is Low Ho must go*
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P value = significant level (sig)
A pvalue 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.
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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 ttest
Stat>B.S.>1 Sample t
2 Sample ttest
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
MultiVari 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
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 Fall '19
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