difference between SRF and PRF graphically?and same ghraph would helpful the concept of Rsquare?
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Answer:
Compare and contrast between the following concepts:
Estimator and estimate An estimator is simply a rule or formula that tells us how to go about estimating a population quantity, such as population mean. An estimate is simply the numerical value taken by an estimator.
Correlation and causation: Correlation measures the degree of linear association of two
Variables, how closely the two are related to each other. The causation implies a causal relationship between the dependent variable and independent variable. Two points between the two terms are: 1) the correlation does not necessarily imply the causation, and 2) causation is implied from a theory or previous research results.
PRF and SRF: PRF specifies the relationship (in the population) between the mean (average) value of the depedent variable (Y) corresponding to each value of the independent variable (X). This relationship may be specified algebraically as E(Y½ Xi ) = B1 + B2Xi. Graphically, the population regression line is a line that passes through the conditional means of Y. SRF specifies the relationship (in the sample) between the Yi , estimator of E(Y½ Xi ), or the estimator of the population conditional mean, and its primary determinant X. Algebraically, it may be written as YI = b1 + b2Xi......
Explanation: tbh idk lmao