The document outlines the principles of statistical analysis using SPSS, detailing the definitions of population and sample, as well as the concepts of parameters and statistics. It categorizes the types of scales used in statistics and distinguishes between descriptive and inferential statistics, highlighting various outcome variables and tests applicable to different data types. Additionally, it provides examples of descriptive and inferential statistics methods, including tests for comparing groups.

1. DR SAJID MALIK
B.Sc., MBBS, FCPS (PAK), MRCS(Glasg.), FMIS (Singapore)
ASSISTANT PROFESSSOR OF SURGERY
ALLAMA IQBAL MEDICAL COLLEGE / JINNAH HOSPITAL LAHORE
PAKISTAN
How to Use SPSS for Statistical Analysis

2. Without data, all you are just another
person with an opinion.
Unknown

3. Population and Sample
Population
is the set of all measurements of
interest to the researcher.
Sample
is any subset of measurements selected
from the population.

5. Characteristic of Population and Sample
Parameter:
The set of measurements in a population may be
summarized by a descriptive characteristic, called a
parameter. e.g. average income of household in Pakistan.
Statistic:
The set of measurements in a sample may be
summarized by a descriptive characteristic, called a
statistic. e.g. sample mean

7. Nominal Scale
Male-Female, Well-Sick, Child-Adult, Married Unmarried
Ordinal Scale
Unimproved, Improved, Much Improved. Above average, average, below
average etc.
Intervals Scale
Arbitrary Zero and unit distance e.g. temperature.
Ratio Scale
Height, weight and length etc.

9. Types of Statistics
 Descriptive statistics
deals with enumeration organization and
graphical representation of the data, e.g. Census data.
 Inferential statistics
is concerned with making conclusions about
population characteristics using information
contained in a sample, that is , generalizing from the
specific e.g. an opinion poll, such as the Gallop Poll.

10. Descriptive statistics
Outcome Variables
Categorical Quantitative
Frequencies
Percentages
Measurement of Central Tendency
Mean, Median Mode
Measurement of Variation / Dispersion
Range, variance, Stand deviation

11. Inferential statistics
Outcome Variables
Categorical Quantitative
Two or More Groups
Chi Square test
Parametric Non-Parametric
Two groups Independent t -test
More than two groups ANOVA
Before & after Paired t test
Two groups Mann Whitney u test
More than two groups Kruskal-Wallis test
Before & after McNemar test