TYPES OF VARIABLES, CONTINUOUS, DISCRETE, DEPENDENT, INDEPENDENT, COLLECTION OF DATA PRIMARY SECONDARY, ERRORS, SUMMATION

1. Presented By
AFSHEEN AFFAN

2.  Statistics is the science of collecting,
organizing, presenting, analyzing and
interpreting the data to assist in
making more effective decisions.
OR
 A body of methods dealing with the
collection, description, analysis and
interpretation of information that can
be given in numerical form.

3.  Statistics are aggregate of facts
 Statistics are numerically expressed
 Statistics are affected by multiplicity of
causes
 Statistics are according to reasonable
standard of accuracy
 Statistics are collected in a systematic
manner
 Statistics are collected for a pre-
determined purpose

4.  Statistics are collected in a
systematic manner
 Statistics are collected for a pre-
determined purpose
 Statistics must be comparable to
each other

5. “Statistics are aggregate of facts,
affected to a marked extent by a
multiplicity of causes, numerically
expressed, enumerated or estimated
according to a reasonable standard of
accuracy, collected in a systematic
manner for a pre determined purpose and
placed in relation to each other”

6.  Theoretical Statistics ( formula and
rules)
 Descriptive Statistics ( numerical,
graphical, tabular forms)
 Inferential Statistics ( drawing
conclusion)
 Applied Statistics ( application of
statistics for policy purpose)

7.  It presents facts in a numerical form
 Statistics simplifies complex mass of
data
 Comparison of data becomes easier
 Statistics studies relationship among
different facts
 Statistics studies changes in a
variable
 Statistics helps forecasting

8.  Business and Economics
 Banks
 Insurance
 Sciences

9.  OBSERVATION
 Anything that can be measured or observed
is called an observation
 DATA
 Numbers or measurements that are
collected as a result of observation
 POPULATION
 A population is the set of all units of interest
in a particular study.

10.  SAMPLE
 A sample is a subset of data selected from
population.
 PARAMETER
 A parameter is the value associated with
population.
 STATISTIC
 A statistic is a value computed from a
sample.

11.  Variable
 A variable is a phenomenon that may vary
from one individual or object to another e.g.
height of students in your class etc.
 Constant
 A quantity which is fixed is called a constant
e.g. no. of days in a week, no. of months in
a year etc.

12.  Quantitative Data
 Quantitative data are observations
measured on numerical scale e.g. Data of
heights, weights, marks etc.
 Qualitative Data
 Qualitative data are observations that are
non-numerical e.g. data of beauty,
intelligence etc. we don’t have scale to
measure them.

13.  Discrete Data
 Data whose possible values are countable is
called discrete data e.g. data of prices,
incomes etc.
 Continuous Data
 Data whose possible values are
uncountable and which may assume any
value in an interval is called continuous data
e.g. record of temperature etc.

14.  Quantitative variable
 When the variable to be studied can be
reported numerically, the variable is called
quantitative variable e.g. marks in test of
statistics etc.
 Qualitative variable
 When the characteristic being studied can
not be recorded in numerical form, it is
called a qualitative variable e.g. intelligence,
gender etc.

15.  Discrete Variables
 A discrete variable is one that can assume
only certain values within an interval e.g.
price of rice etc.
 Continuous Variable
 A continuous variable can take on all
possible values within a specified range e.g.
speedometer of car, temperature etc.

16.  Independent Variable
 A variable is called independent variable if it
is not influenced by any other variable e.g.
price of potatoes.
 Dependent variable
 A variable that is being predicted or
estimated is called dependent variable e.g.
quantity demanded of potatoes is dependent
variable because it depends on price of
potatoes.

17.  Primary Data ( first hand data)
 Direct personal observation
 Indirect personal investigation
 Questionnaire method
 Collection through enumerators
 Collection through local sources
 Secondary Data ( processed data)
 Official statistics
 Semi official

18.  Biased Error
 Unbiased Error

19.  Accuracy
 Significant Figures
 Rounding Off Figures
 Multiplication
 Inequalities
 Approximation
 Limits
 Modulus
 Factorials

20.  The operation of summation is symbolized
by the use of greek capital letter Σ .
σ𝑖=1
𝑛
𝑋𝑖 = 𝑋1 + 𝑋2 + 𝑋3 + ⋯ + 𝑋𝑛
Some other notations
❑ Σ𝑋2
→ means square each value of X, and
then sum
❑ Σ𝑋 2
→ means sum the values of X and
then square the total
❑ Σ 𝑋 − 3 → means subtract 3 from each
value of X , and then sum
❑ Σ𝑋𝑌 → means multiply each value of X and
Y and then add

21. THE END