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Statistical Significance

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Statistical Significance. R.Raveendran. Heart rate (bpm) Mean SEM n. In men - 73.34 5.82 10 ... We do not need a stat test of significance, if only : ... – PowerPoint PPT presentation

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Title: Statistical Significance


1
Statistical Significance
  • R.Raveendran

2
Why should we test significance?
Heart rate (bpm) Mean SEM n
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
IDENTICAL b. we can collect data from all
subjects in a population
3
Why should we test significance?
We test SAMPLE to draw conclusions about
POPULATION If two SAMPLES (group means) are
different, can we 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 obtained is spurious? The above
questions can be answered by STAT TEST.
4
  • Stat test
  • Tests whether two groups are statistically
    different from each other
  • Statistically different? Truly different?
  • Not just apparently different

You do not need statistics to say these two are
truly different. Do you?
5
  • But statistics does help us determine which group
    of trees is taller

You do not need statistics to say these two are
truly different. Do you?
6
How to find statistical difference?
7
  • How does a Stat test work?
  • Stat test analyses the data (numbers) submitted
    (by the researcher) to calculate the chances of
    obtaining a difference when there is none i.e.
    probability of obtaining a spurious difference.
  • It does not indicate
  • whether your design is right or wrong
  • 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 obtained
    difference between two groups is REAL or FALSE

8
What does a Stat test infer?
Stat test ? Data ? P value When plt0.05, it
shows that the chances of obtaining a false
difference is less than 5 (1 in 20) plt0.01
1 in 100 plt0.001 1 in 1000 Since we
consider 5 P is small, we conclude that the
difference between groups is TRUE Truth is
something which is most likely to be true and
100 certainty is impossible.
9
How to test statistical significance? State
Null hypothesis Set alpha (level of
significance) Identify the variables to be
analysed Identify the groups to be
compared Choose a test
Calculate the test statistic Find
out the P value Interpret the P
value Calculate the CI of the
difference Calculate Power if
required
10
Thank you
11
Null hypothesis Null hypothesis (statistical
hypothesis) states that there is no difference
between groups compared. Alternative
hypothesis or research hypothesis states 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)
12
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 null
hypothesis is rejected i.e. the difference
between groups is not due to chance.

13
Choosing a stat test Why should we choose a test?
14
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
15
Choosing a stat test
Parametric Non-parametric
Students t test paired t unpaired t Pearsons correlation ANOVA One way two - way Wilcoxon signed rank test rank sum test Spearmans rank correlation Kruskal-Wallis Friedman Chi square test Kolomogorov-Smirnov test
16
Choosing a stat test 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 the suitable test using the table given.
17
  • Choosing a stat test
  • Data type 2. Distribution of data 3. Analysis
    type (goal)
  • 4. No. of groups 5. Design

Table downloaded from www.graphpad.com
18
Table downloaded from www.graphpad.com
19
Calculating test statistic
difference between group means
variability of groups
XT - XC
e.g. t test t
SE(XT - XC)
Determining P Find out the degrees of freedom
(df) Use t and df to find out P using a formula
or critical values table
20
How to interpret P? If P lt alpha (0.05), the
difference is statistically significant If
Pgtalpha, the difference between groups is not
statistically significant / the difference could
not be detected. If Pgt alpha, calculate the
power If power lt 80 - The difference could
not be detected repeat the study with more
n If power 80 - The difference between
groups is not statistically significant.
21
Degrees of Freedom It denotes the number of
samples that a researcher has freedom to choose.
The concept can be explained by an analogy X
Y 10 df 1 X YZ 15 df 2 For
paired t test df n-1 For unpaired t test
df N1N2 - 1
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