Statistical inference and its types

1. STATISTICAL INFERENCE
REPRESENTATORS : SAFIULLAH

2. STATISTICS
1) DESCRIPTIVE 2) INFRENTIAL
ESTIMATION OF PARAMETER
TESTING OF HYPOTHESIS
POINT ESTIMATION INTERVAL ESTIMATION
ESTIMATION OF SIGNAL VALUE
ESTIMATION OF SIGNAL VALUE

3. Statistical Inference:
The process of drawing conclusion about the
whole population on the basis of information obtained from sample taken from the
population is called infrential statistics.it is a major branch of Statistics.
Types of Statistical Inference:
there are two types:
1) Estimation of Parameter
2) Testing of Hypothesis

4. Testing of Hypothesis:
The procedure which enable us whether to accept or reject a
statement or assumption made about the whole population parameter by
using sample observation.

5. Estimation of Parameter:
The process by which we obtained an estimate
of unknown value of the population parameter by using sample observation is
called estimation.
we can estimate the population mean µ by sample mean X.
there are also two types of estimation of parameter
1) Point estimation
2) Interval estimation

6. TYPES OF ESTIMATION OF PARAMETERS
Point Estimation:
when an estimate for the unknown population
parameter is expressed by a single numerical value is called point
estimate and the process is called point estimation
Example: a sample of size yielded the value 8,4,10,5,5,4,9,4,3,7
Estimate the population mean
Sol: the point estimation of Population mean is X,
X= Ʃx/n
X=8+4+10+5+5+4+9+4+3+7 /10
X=5.9

7. Interval Estimation:
when an estimate is expressed by the range of
values is called the interval estimate and the process is called interval
estimation.
e.g if we wish to estimate temperature of a place and we state the
temperature is 29˚C then it is called point estimation
and if we state that temperature is in between 20˚C and 30˚C so it is
called interval estimation.

8. Estimate and Estimator:
An estimate is a numerical value of parameter obtained by
applying certain rules or formula and the formula which is used for
estimation process is called Estimator.
( X = Ʃx/n) = 5.9
Estimation Estimate