DS Oct 22nd 9:18

Do you think the variables are appropriately used? Why or why not?

Does the addition of the control variables make sense to you? Why or why not?

Does the analysis answer the research question? Be sure and provide constructive and helpful comments for possible improvement.

If there was a significant effect, comments on the strength and its meaningfulness.

As a lay reader, were you able to understand the results and their implications? Why or why not?

Multiple regression is a statistical process that is used to analyze the relationship between one dependent variable and more than two independent variables. According to Frankfort-Nachmias et al. (2019), it is a component of bivariate regression, enabling research to evaluate the effect of multiple independent variables on the dependent variable.

 Research question

The research questions examine whether the independent variable can predict the outcome of the dependent variable, thereby understanding the predictive value and importance of the independent variable. In this case, the research questions aim to examine how teaching experience and efficiency affect math utility.

Research question: To what extent does the number of years of math teaching experience predict students' perceptions of math utility?

The null hypothesis

The Null hypothesis, as stated by Frankfort-Nachmias et al. (2019), is about testing the relationship between variables. The null hypothesis states that there is no alignment between dependent and independent variables. It assumes no predictive relationship between the dependent and independent variables. According to the author, if all correlation coefficients are equal to zero, [complete the sentence]. The null hypothesis seeks to determine if the independent variables predict the dependent variable.

The null Hypothesis: The years of teachers' experience and students' mathematical self-efficacy do not significantly predict students' perception of math utility.

What research design would align with this question?

This study would use a quantitative exploratory research design to explore whether self-efficacy and a teacher's years of experience affect students' perception of mathematical utility. Meyers et al. (2024) stressed that exploratory research seeks to evaluate a phenomenon and identify patterns and relationships using multiple regression, allowing the researcher to explore and test the relationship between independent and dependent variables. Helping explain what factors contribute to a particular outcome, the relationship, and its strengths. In addition, exploratory and multiple regression are used in settings such as education.

What dependent and independent variables were used, and how are they measured?

When using multiple regression, variables are categorized into outcome and predictor variables according to Meyers et al. (2024). The dependent variables are explained, and the independent variables typically exceed two. These are the typical uses for predicting or explaining. In this case, the dependent variable, math utility, is presented, while the independent variables, math self-efficacy and the number of years teachers have taught, describe the outcome. The variables selected are continuous. According to Frankfort-Nachmias et al. (2019), variables should be measured on an interval or ratio scale to provide meaningful numerical information, and independent variables can be measured on either scale. In this case, the variables are measured at intervals, as ratios, and continuously.

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