This document provides an overview of descriptive statistics. It defines descriptive statistics as quantitatively describing the main features of data using tables, graphs, and summary measures. Descriptive statistics are widely used because tables and graphs are easy to understand. The document discusses different types of data collections like census, sample surveys, and experiments. It also defines qualitative and quantitative data. It describes how to organize data by forming frequency tables which include classes, frequencies, tally marks, frequency distributions, and percentages. Finally, it provides an example of a frequency distribution and defines related terms like class boundaries, class limits, and class width.

1. Descriptive statistics
WELCOME
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2. Definition for statistics
The practice or science of collecting and analysing numerical
data in large quantities, especially for the purpose of
inferring proportions in a whole from those in a
representative sample.
It deals with all aspects of data including the planning of data
collection in terms of the design of surveys and experiments
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3. Descriptive statistics
Descriptive statistics is the discipline of quantitatively describing the
main features of a collection of information, or the quantitative
description itself.
It is by displaying or describing data by using table, graph and a
summary measures.
This type of statistics is widely used because it is easy to understand
graph and tables .
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4. Data collections
•Census. A census is a study that obtains data from every member of a population. In
most studies, a census is not practical, because of the cost and/or time required.
•Sample survey. A sample survey is a study that obtains data from a subset of a
population, in order to estimate population attributes.
•Experiment. An experiment is a controlled study in which the researcher attempts to
understand cause-and-effect relationships. The study is "controlled" in the sense that the
researcher controls how subjects are assigned to groups and which treatments each
group receives.
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5. Types of data’s
Qualitatitative data : Is a data where what is being recorded
cannot be readily identified with the real numbers. Examples
: colours, size of egg, etc….
Quantitative data : Is a data where what is being recorded
can be identified with the real numbers. Examples :
Age, I.Q., weight, height, etc….
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6. Organizing data
Data organizing can be done by forming a frequency table.
Frequency table consist of :
Classes: Categories for grouping data.
Tally Marks: Counting the number of items in each class.
Frequency: The number of data values (observations) in each
class.
Frequency Distribution: A table listing all classes and their
frequencies.
Percentage: (Frequency / total items) * 100.
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7. Frequency distribution
Cotinine Level # of smokers
0-99 11
100-199 12
200-299 14
300-399 1
400-499 2
500-599 0
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A frequency distribution, which is really just a table where you tally how many items fall in a
certain category.
Lower class limits: 0,100,…
Upper class limits: 99,…
Class boundaries: numbers used to separate classes without gaps; 99.5, 199.5,…
Class midpoints: center of class; 49.5, 149.5, …
Class width: diference between two consecutive lower (or upper) class limits: 100

8. Thank you
By
Giritharan, 10dm10.
Kamesh, 11dm23.
Abdul suban, 12dm01.
Abdul kader, 12dm02.
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