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8.3 Parameters and Statistics

The word 'Parameters' is associated with the population and it is understood as the measure of the characteristics of the population, such as mean and standard deviation etc.

The word 'Statistics' is used for a random sample and it is understood as the measure of the characteristics of the random sample, such as mean and standard deviation etc.

Note : Different symbols are used to denote parameters and statistics.

Inferential or inductive statistics helps us in making an educated guess about the population parameters based on the statistics of its random sample.

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For instance, say

Aim to know: The average (mean) income of families living in the area "Park avenue" in the year 1997-1998. i.e. The population parameter m (in dollars).

Work out this way: Draw a random sample of 200 families and compute their mean income. i.e. the statistic of sample x say $ 120000.

Conclusion (or inference): The population mean (parameter) is close to sample mean (statistic)i.e. mean income of the families living in the area 'Park Avenue' is $ 120000.


8.1 Population
8.2 Sample
8.3 Parameters and Statistic
8.4 Sampling Distribution
8.5 Sampling Error
8.6 Central Limit Theorem
8.7 Critical Region
8.8 Testing of Hypothesis
8.9 Errors in Tesitng of Hypothesis
8.10 Power o a Hypothesis Test
8.11 Sampling of Variables
8.12 Sampling of Attributes
8.13 Estimation
8.14 Testing the Difference Between Means
8.15 Test for Difference Between Proportions
8.16 Two Tailed and one Tailed Tests
8.17 Test of Significance for Small Samples
8.18 Students t-distribution
8.19 Distribution of 't' for Comparison of Two Samples Means Independent Samples
8.20 Testing Difference Between Mens of Two Samples Dependent Samples or Matched Paired Observations
8.21 Chi-Square
8.22 Sampling Theory of Correlation
8.23 Sampling Theory of Regression

Chapter 1

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