This is our Statement of the problem.
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When you have two independent variables and one dependent variable, you can use a multiple regression analysis.
Based on your statement of the problem, it seems like you have a study with two independent variables (instructional approaches: Guided Discovery Learning and Problem-Based Learning) and one dependent variable (post-test scores)
Hi, thank you for your answer
we are looking at which of the two learning approaches is best for improving analytical thinking skills. Will that tool is still applicable?
Hi, thank you for your answer
Dubey Dhanraj Shevendrakumar
we are looking at which of the two learning approaches is best for improving analytical thinking skills. Will that tool is still applicable?
Justine Praxidio To compare the overall effectiveness of the two learning approaches in improving analytical thinking skills you may use Analysis of Variance (ANOVA) subsequently to examine the within-group changes in analytical thinking skills for each instructional approach one may use Paired-sample t-tests. These tools are popularly used in management approaches like Total Quality Management and Six Sigma.
When you have two independent variables and one dependent variable, you typically use a multiple regression analysis. Multiple regression allows you to examine the relationship between the dependent variable and two or more independent variables while controlling for the effects of each variable.
Here's a brief overview of the steps involved in a multiple regression analysis:
Remember that correlation does not imply causation, so even if you find significant relationships, you should be cautious about making causal claims. Additionally, the inclusion of multiple independent variables allows you to assess their unique contributions to explaining the variance in the dependent variable.
If you have categorical independent variables, you might consider using analysis of covariance (ANCOVA) or logistic regression, depending on the nature of your dependent variable.
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