Response

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Means tests
Response variable of interest variable you
collect - Fish, Coral cover, temperature,
salinity, etc Factor variable by which
response is divided categorical - location,
Date, Gender, Species Level components of
factor - Location (Puako, Hilo Bay), Date (Jan,
Feb), Gender (?, ?)
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Parametric vs. Nonparametric
Parametric Means tests have defined assumptions
including normally distributed data Nonparametric
Means tests have few/no assumptions
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Parametric vs. Nonparametric
Parametric means tests require data to be
normal, etc (assumptions) Nonparametric tests
do not require data to be normal (assumptions)
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Parametric vs. Nonparametric
Parametric means tests include 2 sample t-test,
ANOVA Nonparametric means tests include Mann
Whitney (t-test), Kruskal Wallace (ANOVA)
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Hypothesis Testing
Start with a research question Translate that
question into a hypothesis - statement with a
yes/no answer Hypothesis crafted into two
parts Null hypothesis and Alternative
Hypothesis mirror images of each other
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Hypothesis Testing
Hypothesis testing used for making decisions or
judgments Hypothesis a statement that
something is true Hypothesis test typically
involves two hypothesis Null and Alternative
Hypotheses
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TestingTestingOneTwo
Null hypothesis a hypothesis to be tested
Symbol (H0) represents Null hypothesis Symbol
(µ) represents Mean H0 µ1 µ2 (Null
hypothesis Mean 1 Mean 2)
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TestingTestingOneTwo
Research Question Is there a difference in
urchin densities across habitat types? Null
hypothesis The mean number of urchins in the
Deep region are not equal to the mean number of
urchins in the Shallow region H0 µurchins deep
µurchins shallow In means tests the null
is always that means at equal
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TestingTestingOneTwo
Alternative hypothesis (research hypothesis) a
hypothesis to be considered as an alternative to
the null hypothesis (Ha) (Ha µ1 ? µ2 )(Alt.
hypothesis Mean 1 ? Mean 2)
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TestingTestingOneTwo
Research Question Is there a difference in
urchin densities across habitat
types? Alternative hypothesis (research
hypothesis) a hypothesis to be considered as an
alternative to the null hypothesis (Ha) Ha
µurchins deep µurchins shallow
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TestingTestingOneTwo
Research Question Is there a difference in
urchin densities across habitat types? Null
hypothesis The mean number of urchins in the
Deep region are not equal to the mean number of
urchins in the Shallow region H0 µurchins deep
µurchins shallow In means tests the null
is always that means at equal
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TestingTestingOneTwo
Hypothesis testing is all about taking scientific
questions and translating them into statistical
hypotheses with yes/no answers
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TestingTestingOneTwo
Important terms Test statistic answer unique
to each statistical test (t-test t, ANOVA F,
correlation r, regression R2) Alpha (a)
critical value represents the line in the sand
between yes and no is 0.05 P-value
universal translator between test statistic and
alpha
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Hold on, I have to p
P-value approach indicates how likely (or
unlikely) the observation of the value obtained
for the test statistic would be if the null
hypothesis is true A small p-value (close to 0)
the stronger the evidence against the null
hypothesis It basically gives you odds that you
sample test is a correct representation of your
population
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Didnt you go before we left
P-value equals the smallest significance level
at which the null hypothesis can be rejected -
the smallest significance level for which the
observed sample data results in rejection of
H0 If the p-value is less than or equal to the
specified significance level (0.05), reject the
null hypothesis, otherwise, do not (fail to)
reject the null hypothesis
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No, I didnt have to go then
How to we use p? Compare p-value from test to
specified significance level (alpha, a0.05) If
the p-value is less than or equal to a0.05,
reject the null hypothesis, Otherwise, do not
reject (fail to) the null hypothesis
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No, I didnt have to go then
plt 0.05 Reject Null Hypothesis pgt 0.05 Fail
to Reject (Accept) Null