This document provides an introduction and overview of key concepts in statistics. It defines statistics as the collection, analysis, and interpretation of numerical data. Descriptive statistics are used to summarize and organize data, while inferential statistics allow researchers to make generalizations from a sample to a population. The document outlines common terminology in statistics, different types of data and scales of measurement, and how to present data through tables, graphs, and diagrams. Frequency distribution tables, bar diagrams, pie charts, and histograms are discussed as methods for graphical presentation of data.

1. INTRODUCTION TO
STATISTICS
RATHEESH R.L
LECTURER
MURLIDHAR COLLEGE OF NURSING

2. The word statistics comes from the Italian word
statista and German word statistik.
• The term was first used by professor Gottfried
Achenwall in 1949.

3. DEFINITIONS
• Statistics can be defined as numerical data
involving variability and the treatment of such
data.
• Statistics can be defined as collection,
presentation, analysis and interpretation of
numerical data.
croxton&cowden

4. • Statistics is the science of making effective use
of numerical data which is related to collection,
analysis and interpretation of data.
• Statistics is the study of how to collect,
organizes, analyze, and Interpret data.

5. BIOSTATISTICS
• Biostatistics is the method used in dealing with
statistics in the field of health sciences such as
biology, medicine, nursing, public health,
dentistry, pharmacy and physical therapy.

6. USE OF STATISTICS
• It facilitate comparisons.
• It help to answer important research questions
and field in study.
• It simplify the masses of figures
• It helps to formulate or testing hypothesis.
• It helps in prediction
• To understand what tools are suitable for a
particular research study.

7. TERMINOLOGY
• DATA: It is a factual information collected
during research study.
• QUALITATIVE DATA: The variables that
yield observations on which individuals can be
categorized according certain characteristics or
qualities are referred as Qualitative data.
Eg: gender, occupation, marital status

8. • QUANTITATIVE DATA: The variables that
yield observations that can be measured are
considered quantitative data.
Eg: height, weight, blood pressure
• DISCRETE DATA: The data in a whole
number is called discrete data.
Eg: number of children in a family, pulse rate,
ESR, blood sugar

9. • CONTINUOUS DATA: The data which can
be measured in in fractional values.
Eg: height, weight, body temperature

10. SCALES OF MEASUREMENTS
• Measurement is the assignment of numbers to
objects according to specific rules, to
characterize quantities of an attribute.
• It is a system of classifying measurements
according to the nature of measurement and the
type of mathematical operations to which they
are amendable.

11. There are four levels of measurements,
• Nominal measurement
• Ordinal measurement
• Interval measurement
• Ratio measurement

12. Nominal measurement
• It is the lowest of the four levels of measurements
• It involves the assignment of number to represent
categories or classes of things.
• They have no quantitative values
Gender Habitat
male urban
female rural
slum

13. Ordinal measurement
• Ordinal measurement ranks object based on their
relative standing on a specific attribute.
• Order of ranking is imposed on categories.
• It reflect only magnitude, and does not have equal
intervals or an absolute zero point.
Health status Income status
poor low income
fair middle income
good upper income
excellent

14. Interval measurement
• In this level, there is specification of ranking of
objects on an attributes of the distance between
those objects.
• There is more or less equal numerical distance
between intervals.
Eg: Body Temperature
10-20 degree
30-40 degree
50-60 degree

15. Ratio measurement
• It is the highest level of measurement.
• It represent continuous values
• Has an absolute zero point
Biophysical parameters
-weight
-height
-blood pressure

16. TYPES OF STATISTICS
Two types are there,
• descriptive statistics
• inferential statistics

17. DESCRIPTIVE STATISTICS
• It deals with the enumeration, organization and
graphical representation of data.
Eg: census of india
in this all residents are requested to provide
information such as age, gender, religion, marital
status, education, occupation etc.
the data will be arranged into tables and
graphs and describes the characters of the
population.

18. INFERENTIAL STATISTICS
• Inferential statistics provides the procedures to
draw an inference about the conditions that
exist in a large set of observations.

19. DESCRIPTIVE STATISTICS
• Descriptive statistics are used to organize and
summarize data to draw meaningful
interpretations.
• Descriptive statistics also allow the researcher
to interpret the data meaningfully, so that
research questions can be answered completely
and appropriately.

20. Descriptive statistics is classified into,
• Frequency distribution and graphical
presentation
• Measures of central tendency
• Measures of dispersion
• Measures of relationship ( correlation
coefficient)

21. Frequency distribution
• An appropriate presentation of data involves
organization of data in such a manner that
meaningful conclusions and inferences can
drawn to answer the research question.
• Quantitative data are generally arranged under
frequency distribution and presented through
tables, charts, graphs and diagrams.

22. TABLES
• Tabulation means a systematic presentation of
information contained in the data in rows and
columns in accordance with some features and
characteristics.
• A table presents data in a concise, systematic
manner.
• Tabulation is the first step before data is used
for analysis.

23. PRINCIPLES OF TABULATION
• A table should be precise, understandable, and self
explanatory.
• Every table should have title, which is placed at
the top of the table. The title must describe the
content clearly and precisely.
• Items should be arranged alphabetically or
according to size or importance.
• Rows and columns to be compared with one
another should be brought together.

24. • The content of the table should be defined
clearly and fully.
• The unit of measurement must be cleared state.
• Totals can be placed in the bottom of the
columns.
• Reference symbols can be directly placed
beneath the table for any explanatory
footnotes.
• Two or three small table should be preferred to
one large one.

25. PARTS OF TABLE
• Table number: it should be placed on the top of
the table.
• Title: every table must have a suitable title.
• Head notes: it is given just below the title in
brackets for further description of the contents of
the table.
• Captions and stubs: captions are the headings
designated for vertical columns and stubs are the
headings for horizontal rows.

26. • Body of table: arrangement of data according
to description given in the form of captions
and stubs form the body of table.
• Foot notes: when some contents of the table is
not adequately explained, foot notes are used
to explain those items.
• Source notes: source note is used when
secondary data is used to mention the source
from which the data for the table or the table
itself is retrieved.

27. TYPES OF TABLE
• Frequency distribution table
• Contingency table
• Multiple response table
• Miscellaneous table

28. Frequency distribution table
• A frequency distribution is a table that displays
the frequency of various outcomes in a sample.
• Each entry in the table contains the frequency or
count of the occurrences of values within a particular
group or interval, and in this way,
the table summarizes the distribution of values in the
sample.

30. Contingency table
• A table showing the distribution of one
variable in rows and another in columns, used
to study the correlation between the two
variables.

32. Multiple response table
When classification of the cases is done into
categories that are neither exclusive nor
exhaustive, we get what is called multiple
responsible table.

34. Miscellaneous table
• These tables are used to present data other than
frequency or percentage distributions such as
mean, median, mode, range, standard deviation
etc.
• A table is called miscellaneous when presentation
of data cannot be classified under the frequency
distribution table, contingency table or multiple
response table.

35. Graphical presentation of data
• Commonly we are using graphs and diagrams
for presenting the data of research studies,
which include bar diagram, pie diagram,
histogram, frequency polygon, line graphs,
cumulative frequency curves etc.

36. USES
• They gives an overall view of entire data.
• They are visually more attractive than other
ways of presenting data.
• It is easy to understand and memorize.
• It facilitate comparison of data.

37. Construction of diagrams and
graphs
• They must have a title
• The proportion between width and height be
balanced.
• The selection of scale must be appropriate.
• Footnotes may be included wherever it is
needed.

38. Types of diagram and graphs
• The types include
– bar diagram
– pie diagram
– Histogram
– frequency polygon
– line graphs
– cumulative frequency curves

39. BAR DIAGRAM
• It is a convenient, graphical device that is
particularly useful for displaying nominal or
ordinal data.
• It is an easy method adopted for visual
comparison of the magnitude of different
frequencies.
• Length of the bars drawn vertically or
horizontally indicates the frequency of character

40. • If the bars are placed vertically it is called as
vertical bar charts.
• When the bars are placed horizontally, then it
is known as horizontal bar charts

42. Points to remember…
• The width of the bars should be uniform
throughout the diagram.
• The gap between the bars should be uniform
through out
• Bars may be vertical or horizontal

43. Types of bar diagram
• SIMPLE BAR DIAGRAM
• MULTIPLE BAR DIAGRAM
• PROPORTION BAR DIAGRAM

44. SIMPLE BAR DIAGRAM

45. MULTIPLE BAR DIAGRAM

46. PROPORTION BAR DIAGRAM

47. PIE DIAGRAM
• It is another useful pictorial device for
presenting the data.
• The total area of the circle represents the entire
data under consideration.
• The total angle of pie diagram should be 360
degree.

48. PIE DIAGRAM/ SECTOR DIAGRAM

49. HISTOGRAM
• It is the most commonly used graphical
representation of grouped frequency distribution.
• Variable characters of different groups are
indicated on horizontal line (x-axis) and the
frequencies (number of observation) are indicated
on the vertical line (y-axis).