![]() ![]() ![]() Likelihood to use a product or service again.Likelihood to recommend a product or service.Overall satisfaction with a product or a service.Common dependent variables in survey analysis applications of regression include: In the example above the dependent variable is sales. Most regression models are characterized by having one dependent variable and one or more independent variables. For example, the equation above shows that TV advertising is more effective than online advertising. ![]() Draw conclusions about relative effectiveness.For example, using the formula above, a firm that spends $1,000,000 on TV advertising and nothing on advertising expenditure is predicted to have sales of $121 + 4.1 × $1,000,000 = $4,100,121. $Sales = $121 + 4.1 × $TV Advertising Expenditure + 3.2 × $Online Advertising Expenditure The key output of regression is a formula, such as: Regression is a statistical tool for quantifying a model. ![]()
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