Question

Explain the applications of correlation and regression analysis in geographical studies

Answer 1

Answer:

In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome variable') and one or more independent variables (often called 'predictors', 'covariates', or 'features'). The most common form of regression analysis is linear regression, in which a researcher finds the line (or a more complex linear function) that most closely fits the data according to a specific mathematical criterion. For example, the method of ordinary least squares computes the unique line (or hyperplane) that minimizes the sum of squared distances between the true data and that line (or hyperplane). For specific mathematical reasons (see linear regression), this allows the researcher to estimate the conditional expectation (or population average value) of the dependent variable when the independent variables take on a given set of values. Less common forms of regression use slightly different procedures to estimate alternative location parameters (e.g., quantile regression or Necessary Condition Analysing or estimate the conditional expectation across a broader collection of non-linear models (e.g., nonparametric regression).

Regression analysis is primarily used for two conceptually distinct purposes. First, regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning. Second, in some situations regression analysis can be used to infer causal relationships between the independent and dependent variables. Importantly, regressions by themselves only reveal relationships between a dependent variable and a collection of independent variables in a fixed dataset. To use regressions for prediction or to infer causal relationships, respectively, a researcher must carefully justify why existing relationships have predictive power for a new context or why a relationship between two variables has a causal interpretation. The latter is especially important when a researcher hopes to estimate causal relationships using observational data.

Answer 2

Explanation:

Ans. The following are the advantages of study regions by following application of geographic knowledge:

(1) Study of regions by following application geographical knowledge helps in understanding the characteristics of the region.

(2) It helps in understanding how people h adapted to the region.

(3) It helps in understanding the problems arisie

due to over exploitation of natural resources in the

region.

(4) It helps in understanding the measures to be taken against the degradation of environment.

(5) It enables to look at the current trends and understanding the process of changes occurring.

(6) It helps to face natural and man-made disasters

in better way.

(7) It helps in knowing the reasons for regional imbalance and understanding the possible remedies.

(8) It enables to predict what will happen in future.

.

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