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Best Approaches to Regression Analysis Data

regression analysis data

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Regression analysis in comparison with exploratory data analysis tukey or inferential statistical analysis is all about variables. It looks at relationships that and Bennett variable may have with A number of independent variables and give some idea of what happens to the dependent variable when something new is added. This type of statistical analysis is used in forecasting and shows the influence of independent variables. There are certain situations where regression data analysis can be particularly useful.

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Some Areas of Particular Advantage for Regression Data Analysis

what to be considered the best use for regression analysis of data is in marketing research. It permits the study of relationships that arise between independent and dependent variable. Sales may be the dependent variable and various marketing strategies would be the independent variables. In this case. The analysis is able to better indicate if something such as pricing has a desired impact. The predictive value is also important. Marketing budgets are notoriously tight. Having an idea of what impact a given independent variable has will better direct budget resources.

Regression Analysis Data Has High Accuracy

a superior approach to the data would be in various measures. The objective measures used, to study the variable relationships produce better information. Regression models also help strengthen production accuracy with the use of R – square and T – value statistics. The regression analysis moves things away from personal bias or judgment into more objective conclusions. These can influence the decisions that need to be made.

Management Decisions Become Better Focused

it is because the data replaces hunches, and the impacts are statistically shown. Marketing is not the only area where regression analysis helps management. Customer service is enhanced as the buying patterns of repeat customers are evaluated against the dependent sales variable. Six Sigma is a very important tool for internal corporate development. Causal relationships can be evaluated to determine how they will affect needed change within the corporate environment.

Small business can benefit from regression analysis and software that has regression analysis capabilities. One of the problems that entrepreneurs face is an overreliance on intuition. This happens because of an inability to assess large amounts of data. Regression analysis and the inherent forecasting techniques can help. Large amounts of data from customer surveys and transactions can be analyzed using the right software. It can help small business make better, more cost-effective decisions.

It can happen that mistakes are made in any number of decisions. Regression analysis can either support or show the weaknesses of what is being implemented. An example would be whether or not sales are increased appreciably when a store is open on a holiday, as opposed to extended hours on a given day of the week. A small business can also discover new ways of improving chances of profit. Small things hidden in the statistics can suggest possible innovations. It is found in revealing how a given independent idea makes impression on sales figures.

Regression analysis is best done using software and there are number of packages available on the market. Management can use regression analysis for issues with evolving sales, customer service, and improvements to be made in the corporate environment.

This is a very powerful tool in the hands of decision-makers, and those people should not hesitate in using it!