Data analysis using multiple regression analysis is a fairly common tool used in statistics. Many graduate students find this too complicated to understand. However, this is not that difficult to do, especially with computers as everyday household items nowadays. You can now quickly analyze more than just two sets of variables in your research using multiple regression analysis.
How is multiple regression analysis done? This article explains this handy statistical test when dealing with numerous variables then provides an example of a research using multiple regression analysis to demonstrate how it works. It explains in detail how research using multiple regression analysis is conducted.
Statistical Software Applications Used in Computing Multiple Regression Analysis
Multiple regression analysis is a powerful statistical test used in finding the relationship between a given dependent variable and a set of independent variables. The use of multiple regression analysis requires a dedicated statistical software like the popular Statistical Package for the Social Sciences (SPSS), Statistica, Microstat, and open-source statistical software applications like SOFA statistics and Jasp, among other sophisticated statistical packages. Two decades ago, it will be near impossible to do the calculations using the obsolete simple calculator replaced by smartphones.
However, a standard spreadsheet application like Microsoft Excel can help you compute and model the relationship between the dependent variable and a set of predictor or independent variables. But you cannot do this without activating first the setting of statistical tools that ship with MS Excel.
Activating MS Excel
To activate the add-in for multiple regression analysis in MS Excel, you may view the two-minute Youtube tutorial below. If you already have this installed on your computer, you may proceed to the next section.
Example of a Research Using Multiple Regression Analysis
I will illustrate the use of multiple regression analysis by citing the actual research activity that my graduate students undertook two years ago. The study pertains to identifying the factors predicting a current problem among high school students, that is, the long hours they spend online for a variety of reasons. The purpose is to address many parents’ concerns on their difficulty of weaning their children away from the lures of online gaming, social networking, and other engaging virtual activities.
Review of Literature on Internet Use and Its Effect on Children
Upon reviewing the literature, the graduate students discovered that very few studies were conducted on the subject matter. Studies on problems associated with internet use are still in its infancy as the Internet has just begun to influence everyone’s life at that time.
Hence, with my guidance, the group of six graduate students consisting of school administrators, heads of elementary and high schools, and faculty members proceeded with the study.
Given that there is a need to use a computer in analyzing multiple variable data, a principal who is nearing retirement was “forced” to buy a laptop as she had none. Anyhow, she is very much open-minded and performed the class activity with much enthusiasm.
The Research on High School Students’ Use of the Internet
The brief research using multiple regression analysis is a broad study or analysis of the reasons or underlying factors that significantly relate to the number of hours devoted by high school students in using the Internet. The regression analysis is broad because it only focuses on the total number of hours devoted by high school students to activities online.
The time they spent online was correlated with their profile. The students’ profile consisted of more than two independent variables, hence the term “multiple.” The independent variables are age, gender, relationship with the mother, and relationship with the father.
The statement of the problem in this study is:
“Is there a significant relationship between the total number of hours spent online and the students’ age, gender, relationship with their mother, and relationship with their father?”
Their parents’ relationship was gauged using a scale of 1 to 10, 1 being a poor relationship, and 10 being the best experience with parents. The figure below shows the paradigm of the study.
Notice that in research using multiple regression studies such as this, there is only one dependent variable involved. That is the total number of hours spent by high school students online. Although many studies have identified factors that influence the use of the internet, it is standard practice to include the respondents’ profile among the set of predictor or independent variables.
Hence, the standard variables age and gender are included in the multiple regression analysis. Also, among the set of variables that may influence internet use, only the relationship between children and their parents were tested. The intention of this research using multiple regression analysis is to determine if parents spend quality time establishing strong emotional bonds between them and their children.
Findings of the Research Using Multiple Regression Analysis
What are the findings of this exploratory study? This quickly done example of a research using multiple regression analysis revealed an interesting finding.
The number of hours spent online relates significantly to the number of hours spent by a parent, specifically the mother, with her child. These two factors are inversely or negatively correlated. The relationship means that the greater the number of hours spent by the mother with her child to establish a closer emotional bond, the fewer hours spent by her child using the internet. The number of hours spent by the children online relates significantly to the mother’s number of hours interacting with their children.
While this example of a research using multiple regression analysis may be a significant finding, the mother-child bond accounts for only a small percentage of the variance in total hours spent by the child online. This observation means that other factors need to be addressed to resolve long waking hours and abandonment of serious study of lessons by children. But establishing a close bond between mother and child is a good start.
The above example of a research using multiple regression analysis demonstrates that the statistical tool is useful in predicting dependent variables’ behavior. In the above case, this is the number of hours spent by students online.
The identification of significant predictors can help determine the correct intervention to resolve the problem. The use of multiple regression approaches prevents unnecessary costs for remedies that do not address an issue or a question.
Thus, in general, this example of a research using multiple regression analysis streamlines solutions and focuses on those influential factors that must be given attention.
©2012 November 11 Patrick Regoniel
Updated: 14 November 2020