Summary of Statistic Analysis Essay

601 Words Nov 6th, 2012 3 Pages
Statistical is an explanation type in social science trough credible causal mechanisms such as quantitative reasoning, statistical analysis and comparative, and statistic explanation et cetera. Basic of statistical explanation, there are two points which are understanding of concept and second is questions. In terms of statistical analysis, researcher needs the collection, summarization, manipulation, and interpretation of quantitative data to discover its underlying causes, patterns relationships and trends.
In the quantitative reasoning in social science, the data set is involved into the structure. Data which involve might be a time-series data set for study to a time sequence or complex data which researcher has
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• Negative correlation: the variables deviate in opposite direction.
Linear and Non – Linear correlation
• Linear correlation: the change of one unit in one variable result in the corresponding change in the other variable over the entire range of values.
• Non - Linear correlation: corresponding to a unit change in one variable, the other variable does not change at a constant rate but changes at a fluctuating rate
Coefficient of correlation: measures the degree of association between the two values of related variables given in the data set. Regression
Regression is two variables are significantly correlated it is possible to predict values of one variable from the other It is specially used in business and economics to study the relationship between two or more variables that are related causally and for the estimation of demand and supply graphs, cost functions, production and consumption functions and so on. If we have two sets as X & Y We can predict the values of ‘Y’ given the values of ‘X’ by using the equation:
(Y = MX + B).
Philosophical grounds of statistical explanation We need to operationalize the theoretical hypothesis in terms of observable variables.
A statistical study can provide empirical grounds for accepting or rejecting a casual hypothesis, but the statistical findings themselves are not final or conclusive. Study of

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