statistics, medical statistics, scientific paper, statistical analysis, use of statistical test

1. STATISTICAL METHODS

2. Medical Statistics
Prof.Dr.Amany Rashad Aboel-Seoud
Community Medicine Department
Zagazig university

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

5. Medical Statistics
STATISTICAL
ANALYSIS
useful
INFORMATION
In medical field
DATA
(accuracy)

6. DATA
SOURCES
Records, Census
Survey, Research studies
(sampling)
PRESENTATION
Tables
Summarization
Graphs
Analysis &
interpretation
information
Planning for health programs

8. population

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

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

25. Types of correlation
+ve
-ve
No

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

43. Wilcoxon test, Mann Whitney test

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

65. Thank you