The document discusses different types of data that can be collected from a student survey. It defines data as observed values of variables, which are characteristics of objects. There are two main types of data: categorical and numerical. Categorical data includes nominal data, which are labels without order, and ordinal data, which have a meaningful order but unequal intervals. Numerical data can be discrete, involving whole numbers by counting, or continuous, involving fractions by measuring. Age is continuous while chocolates eaten is discrete. The document provides examples to illustrate the differences between these data types.

1. Data
MODULE 1.2

2. TOPICS TO BE COVERED
Students Survey
What is Data?
Types of Data

3. Student Survey

4. Sample Student Survey Form
Name of the Student:______________________________
1. What is your age?______________________ (in years)
2. Specify your Gender.
Male Female
3. Which city you prefer in MP.
Indore Bhopal Gwalior
4. How many chocolates you eat in a day.______________(Units)
5. Rate Chennai “BOL BACHAAN” Express Movie:
Haven’t Seen 1 Star 2 Stars 3 Stars 4 Stars 5 Stars
6. How many movies you watch in a month.______________(Units)

5. WHAT YOU ARE SUPPOSE TO
DO?Ch?oo?se one question and summarize the results.
 Analyze the difference between the questions and
response.

6. What is Data?????

7. DATA
 Data are the observed values of a variables.
 Variables are any characteristics of our objects or
observation.
 An object can be:
People Laptops Mobiles Class Room

8. DATA
 For example, Students in this class are Objects
 Their characteristics can be age, gender, height
etc
 These are the variables, because this would vary
from person to person.
 And if we put this data into a table or a
spreadsheet, then

10. DATA
 The data can be obtained by:
 Measuring (height or weight)
 Counting
 Asking (marital status or graduation)
 Observing (gender or skin color)
 Computing (BMI)

11. Types of Data

12. TYPES OF
DATA
 The type of data determines which:
 Summary Statistics
 Graphs
 Analysis
 Are possible and sensible to be applied on the
object?

13. TYPES OF
DATA
CATEGORICAL
DATA
 This kind of data deals with the QUALITATIVE
options of the objects.
 For example, gender, marital status.
 Usually questions about categorical data are
answered with words.

14. MALE-FEMALE V/S CHENNAI
EXYPou say that both these data are qualitative
or categorical.
 Then is there any difference between the two.
Gender
 Objective Kind
 Its not ranking, its just word
or labels with no rank or
order.
 There is no such logic put
in.
Movie Rating
 Subjective Kind
 Ranking is carried out, from
lowest to highest in a order.
 Logic of rating may differ
from person to person.

15. CATEGORICAL DATA
 As there can be different kind of qualitative
data, thus we need a different kind of scale to
measure them.

16. TYPES OF
DATA
CATEGORICAL
DATA
NOMINAL
LEVEL  It is the most basic level of
measurement of the variable.
 These are descriptions or labels
with no sense of sequence.

17. NOMINAL LEVEL
GENDERS
PREFERED
CITY IN MP
COLORS
 These are descriptions or labels.
 With no sense of sequence or
order.
 These can stored as word or text
or can be given a numerical
code.
•MALE
•Indore •FEMALE
•Bhopal
•Gwalior
•RED
•BLUE
•YELLOW
•WHITE
1. MALE
1. Indore 2. FEMALE
2. Bhopal
3. Gwalior
1. RED
2. BLUE
3. YELLOW
4. WHITE
 To summarize a nominal
data we use frequency or
percentage.
 We cannot calculate mean
or average value of nominal
data.

18. TYPES OF
DATA
CATEGORICAL
DATA
NOMINAL
LEVEL
ORDINAL
LEVEL

19. ORDINAL LEVEL
•Ecstasy
•Delight
•Satisfied
•Not Satisfied
•1st Rank
•2nd Rank
•Rank
•1st Rank (98.3%)
•2nd Rank (97.2%)
•3rd Rank (92.3%)
SATISFACTION RANK
 They have meaningful order.
 But the intervals between the values in this
scale may not be equal.
 Like nominal data, ordinal data can be given
as frequencies or percentages.

20. TYPES OF
DATA
NUMERICAL
DATA
CATEGORICAL
DATA
NOMINAL
LEVEL
ORDINAL
LEVEL
 This kind of data deals
with the
QUANTITATIVE options
of the objects.
 This includes things,
which can be measured
rather which can be
classified or ordered.

21. AGE V/S CHOCOLATE
COYoNuS saUyM thPatT bIoOthN these data are quantitative
or numeric.
 Then is there any difference between these
two.
Age
 Measurement or Calculation is
done
 Its kind of a continuous data,
and the accuracy of exact age
may typically depend on the
units used.
 It can be in fractions.
Chocolates
 Counting
 Its kind of fixed numbers.
 It will generally be in a whole
number.

22. TYPES OF
DATA
NUMERICAL
DATA
CATEGORICAL
DATA
NOMINAL
LEVEL
ORDINAL
LEVEL
DISCRETE
DATA

23. DISCRETE DATA
Number of
questions in a
paper
Number of
students in
the class
 These are quantitative data with whole numbers.
 A type of data is discrete if there are only a finite number of
values possible.
 Discrete data usually occurs in a case where there are only
a certain number of values, or when we are counting
something.

24. TYPES OF
DATA
NUMERICAL
DATA
CATEGORICAL
DATA
NOMINAL
LEVEL
ORDINAL
LEVEL
DISCRETE
DATA
CONTINUOUS
DATA

25. CONTINUOUS DATA
Weight
Height
 These are quantitative data with fractional numbers.
 Continuous data makes up the rest of numerical data. This is a
type of data that is usually associated with some sort of physical
measurement.
 Continuous data usually occurs in a case where we are measuring
or calculating something.
 One general way to tell if data is continuous is to ask yourself if it
is possible for the data to take on values that are fractions or
decimals. If your answer is yes, this is usually continuous data.

27. TYPES OF
DATA
NUMERICAL
DATA
CATEGORICAL
DATA
NOMINAL
LEVEL
ORDINAL
LEVEL
DISCRETE
DATA
CONTINUOUS
DATA