A to Z Statistical Significance GET IT NOW

8/14/2019 A to Z Statistical Significance GET IT NOW

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Dr Sherwan R Shal


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Heart rate (bpm) Mean SEMn

In men - 73.34 5.82 10

In women - 80.45 6.13 10

The difference between means (80.45-73.34) =7.11

We do not need a stat test of significance, if only:

a. the data from all subjects in a group are

Why should we test significance?


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We test SAMPLE to draw conclusions aboutPOPULATION

If two SAMPLES (group means) are different, canwe be certain that POPULATIONS (from which the

samples were drawn) are also different?

Is the difference obtained TRUE or SPURIOUS?

Will another set of samples be also different?

What are the chances that the difference obtainedis spurious?

The above questions can be answered by STATTEST.

Why should we test significance?


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But statisticsdoes help usdetermine

which groupof trees is

taller

You do not need

statistics to saythese two are trulydifferent. Do you?


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How does a Stat test work?

Stat test analyses the data (numbers) submitted

(by the researcher) to calculate the chances ofobtaining a difference when there is none i.e.probability of obtaining a spurious difference.

It does not indicate(a) whether your design is right or wrong(b) whether the type of data is correct or wrong(c) the magnitude of the difference(d) whether the difference will be practically useful

All it can point out is whether the obtaineddifference between two groups is REAL or FALSE


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What does a Stat test infer?

Stat test Data P valueWhen p


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How to test statistical significance?

State Null hypothesisSet alpha (level of significance)

Identify the variables to be analysedIdentify the groups to be compared

Choose a test

Calculate the test statisticFind out the P value

Interpret the P valueCalculate the CI of the differenceCalculate Power if required


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Null hypothesis

Null hypothesis (statistical hypothesis) states thatthere is no difference between groups compared.

Alternative hypothesis or research hypothesisstates that there is a difference between groups.

e.g.

New drug X is an analgesic - (Research

hypothesis)New drug X is not an analgesic (Null hypothesis)


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Alpha / type 1 error / level of significance

The level of significance is to be set

It is generally set at 0.05 (5%) and not above.

If the P value is less than this limit then nullhypothesis is rejected i.e. the differencebetween groups is not due to chance.


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Choosing a stat test

Why should we choose a test?


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Choosing a stat test.

Why should we choose a test?

There are many tests

The selection of test varies with the type of

data,analysis,study design,

distribution &no. of groups


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Parametric Non-parametric

Students t testpaired t

unpaired t

Pearsonscorrelation

ANOVA One way

two - way

Wilcoxonsigned rank test

rank sum test

Spearmans rankcorrelation

Kruskal-WallisFriedman

Chi square test

Kolomogorov-Smirnov test


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Determine :

Aim of the study Parameter to be analysed -Data type- [Continuous, Discrete, Rank, Score,

Binomial]

Analysis type- [Comparison of means, Quantify association,Regression analysis]

No. of groups to be analysed -No. of data sets to be analysed -Distribution of data - [normal or non-normal]Design - [paired or unpaired]

With the above information, one can decide thesuitable test using the table given.


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3. Data type 2. Distribution of data 3. Analysis type (goal)

4. No. of groups 5. DesignTable downloaded fromwww.graphpad.com


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Table downloaded fromwww.graphpad.com


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Calculating test statistic

difference between group means

variability of groups

XT - XC

SE(XT - XC)e.g. t test te.g. t test t==

Determining PDetermining P

Find out the degrees of freedom (Find out the degrees of freedom (dfdf))

UseUse ttandand dfdfto find outto find out PP using ausing a

formula or critical values tableformula or critical values table


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How to interpret P?

If P < alpha (0.05), the difference is statisticallysignificant

If P>alpha, the difference between groups is notstatistically significant / the difference could

not be detected.

If P> alpha, calculate the power

If power < 80% - The difference could not bedetected; repeat the study with more nIf power 80 % - The difference betweengroups is not statistically significant.


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Degrees of Freedom

It denotes the number of samples that aresearcher has freedom to choose.

The concept can be explained by an analogy :

X + Y = 10 df = 1 X+ Y+Z = 15 df = 2

For paired t test df= n-1

For unpaired t test df= N1+N2 - 1

A to Z Statistical Significance GET IT NOW

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