3. Definition of statistics
• It is the science and art of dealing with
numbers.
• Used for collection, summarization,
presentation and analysis of data to get
information based on objective basis (un-
biased).
4. Uses of statistics
• Descriptive information for any
population
• Prove association between variables
• Prove relation between risk and disease
• Compare two studied groups (or more)
• Evaluate health programs & services
15. Inferential Statistics
• Put a hypothesis
X = Y H0 or X >Y H1 or Y>X H2
• Collect, summarize data
• Test your hypothesis using tests of significance:
Comparison of mean values : t , paired t test & ANOVA
(used for numeric continuous data)
Finding relations between different variables using
Correlation & regression tests
16.
17.
18.
19.
20.
21.
22.
23. Correlation test
To find a relation between 2/more variables in
direction & strength (one is dependent =
response. It is plotted on the y axis) &(the
other/s is independent = explanatory or risk. It is
plotted on the x axis)
• Correlation does not mean causation.
• Spurious correlation: significant statistically but
insignificant clinically
26. Coefficient of correlation “r” ranges from 0 to 1 It is
either +ve or -ve in direction
(r=0.5 p=0.02), (r=- 0.6,p=0.01) (r= 0.1,p=0.98)
Coefficient of determination R 2 : to quantify the variation of
one variable that is contributed to the other variable.
Types of correlation:
I) single (simple) & multiple
II) Pearson : numeric, normally distributed, linear
Spearman : ordinal, non linear, not normally distributed
27. Regression analysis
To predict a dependent variable from another known
variable (s).
• Linear: dependent = intercept +/- b coefficient x
independent variable
e.g. birth wt = y +/- b x gestational age
= 0.21 + 5 x 36
• Multiple
e.g. Birth wt= y +/- b1*gest+/- B2*HC
48. Analysis of qualitative data
(1) Chi squared test : to find significant relation
between 2 variables or order distributions or
categorical data.
(2) Difference between proportions (z test)
as t test but use percentage instead of mean
values