National open university of nigeria introduction to econometrics II eco 356


Table 1.1.1 Simple Random Sampling



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Introduction to Econometrics ECO 356 Course Guide and Course Material
Introduction to Econometrics ECO 356 Course Guide and Course Material
Table 1.1.1 Simple Random Sampling

Samples

Probability

mean

Variance
(0,2)


1 2
(0,4)


2 8
(0,6)


3 18
(2,4)


3 2


INTRODUCTION TO ECONOMETRICS II

ECO 306

NOUN
25

(2,6)


4 8
(4,6)


5 2 We see in this example that V (
̅)

.

/


/


/
Similarly,
(
) .

/



…[1.14]
Could also be obtained from table 1.1.1
1.1.3.5 Estimation of Population Mean
If we are interested in estimating a population mean from a simple random sample, we have
̂
̅







…[1.15]
If we are interested in estimating population variance from a simple random sample, we have
̂( ̅)

.

/



…[1.16]
Where,


(

̅ )






…[1.17]
When the margin of error is two standard errors, we have

̂( ̂) √

.

/


…[1.18]
1.1.4.0SUMMARY


INTRODUCTION TO ECONOMETRICS II

ECO 306

NOUN
26 In this unit, the students are presented with the essentials and applications of the concept of random variables and sampling theory and their estimations. Also, by now the students should be able to identify functions and problems associated with the estimation.
1.1.5.0 CONCLUSION
In this unit, the concepts of random variables and sampling theory have been introduced and discussed and the associated estimation explained. The students are made to understand that random variables are of two quantitative (discrete and continuous random) variable types, whose values maybe determined through the outcome of a random trials. D
iscreteand continuous random variables were both explained with examples. Further definition of random variable as it relates to a population is explained. Furthermore, inference is made on how the student may apply the random variable in other statistical analysis like mean, variance, standard deviation, etc. Sampling theory is introduced in this unit inform of comparison to random variable. Some terminologies and reasons associated with sampling are also discussed. Probability and non- probability sampling techniques are presented as two sample designs methods that utilise planned randomness. Although, in practice, other more sophisticated probability sampling and estimation methods are commonly used, the unit focused on simple random sampling and population mean techniques as starting points.

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