8210 WK9 DISCUSSION
Response 1
Steven stoner
RE: Discussion - Week 9
Top of Form
Frankfurt-Nachmias, 2020 stated that multiple regression estimates how several independent variables affect one dependent variable. Using the High School Long Study Data Set and SPSS Software, a multiple regression model was used to examine the relationship between a student's math identity, their math self-efficacy, and their math utility. The High School Long Study Data Set has a mean socio-economic status of .0661. The mean of .0661 would lead one to believe that the respondents leaned more middle class in the social class structure.
Research Question
Using the High School Long Study Data Set, a research question was developed using the multiple regression model. The dependent variable is the scale of a student's mathematical identity. The two independent variables used are the scale of a student's mathematics self-efficacy and the scale of a student's mathematical utility. The question is essential to help teachers understand how students learn math and what should be done to help students build their math skills.
The research question developed is: Do students' mathematical identity increase as their mathematics self-efficacy and utility increase?
The null hypothesis for the question is that a student's mathematical identity is not affected by mathematical self-efficacy and utility.
Multiple Regression Analysis
The multiple regression model was used to determine how a student's mathematics utility and self-efficacy would affect their mathematics identity. Looking at Table 1, under the unstandardized coefficients, a student's mathematic self-efficacy increases for every unit, and their mathematic identity would increase by .55 units. Also, for every unit a student's mathematic utility increases, their mathematic identity will increase by .128 units (Walden, 2016). The significance level for both independent variables was below .05 at .001, so the null hypothesis may be rejected. Since the null hypothesis is refected, it can be said that a student's mathematic self-efficacy and utility significantly affect a student's mathematic identity.
The effect size for a student's mathematic identity is .349, representing a medium effect; as the effect size increases, the significance increases (Wagner, 2020). The medium effect shows that the results are meaningful as well.
Table 1
Multiple Regression Coefficients
Conclusion
Understanding how multiple variables can affect one aspect of a student's learning is essential. Using the multiple regression model will allow educators to gather information on various levels and from numerous sources to create the best plans. The test showed that self-efficacy, one's belief that they can do it, and utility, one's satisfaction with learning, can increase one's identity or how they see themselves as learners of a subject. Understanding that is important for all learners and subjects makes the research meaningful.
References
Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Sage Publications.
Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Sage Publications.
Walden University, LLC. (Producer). (2016). Multiple regression [Video file]. Author.
Bottom of Form
RESPONSE 2
Carey-Ann Thurlow
RE: Discussion - Week 9
Top of Form
Multiple Regression
Pearson’s correlation is utilized to examine associations among variables, and allows researchers to examine how a variable changes as other variables change. Researchers use this method when examining two or more interval-ratio or continuous variables (Walden University, 2022). When examining variables using a multiple regression model, researchers pay close attention to the R-squared statistic. R-squared is an important statistic, as it displays the proportion of variability in the dependent variable that is accounted for by in the data being tested (Walden University, 2022). R-squared tells the researcher how good the predictors are at predicting the outcome variable (Walden University, 2022).
Using the Afrobarometer SPSS dataset, the following post answers the research question; ‘Does trust in the government decrease with an increase in participants’ problems with public schools and problems with public health clinics?’. The Afrobarometer research study collects information from four different regions in Africa to evaluate the values and experiences of the African people (PARN, 2022). The mean age of the individuals included in the Afrobarometer study is 37.14, and is important to consider in relation to perceptions of government trust in relation to issues participants may have had with public health and public schools.
In Table 1 (below), the adjusted R-square is slightly different than the R-square. Only 4.8% of the variability in respondents’ trust in government is explained by the combination of the two independent variables, problems with public health clinics and problems with public schools.
Table 1
Multiple Regression Summary of the Dependent and Independent Variables
The ANOVA test verifies that this model is significant with p<.001. If this model was not significant, researchers would want to take caution in interpreting it, or choosing different variables to analyze.
Table 2
ANOVA test for the Dependent and Independent Variables
The constant is a mathematical anchor where the regression line crosses the Y axis. This is now controlling the effects of other independent variables, where for every one unit increase in the independent variable, the dependent variable changes by the value of the unstandardized coefficient. So, for every one unit increase in problems with public schools, the value in citizen’s trust in government will decrease by.093 units, controlling for the variable problems with public health clinics.
Table 3
Standardized and Unstandardized Coefficients test for the Dependent and Independent Variables
Therefore, with a significance of p<.001, the data can be assessed as; problems with public schools and problems with public health clinics are significant predictors of the level of trust the respondents have in the government. In addition, researchers can determine if the association between the variables is weak, moderate or strong, based on the standardized coefficient value range of -1 to 1 (Walden University, 2022). Although, the test shows significance at p<.001, the standardized coefficients are a weak negative at -.115 and -.128.
The null hypothesis stating that there is no correlation between participants’ trust in government in relation to their perception of problems with public schools and problems with health clinics can be confidently rejected with a significance of p<.001.
References
Billings, J., (n.d.). Primary guide to research statistics: A monograph for use with ED: 8900 courses. https://content.waldenu.edu/d1c00f22444bfb7cf79c9487accceada.html
Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G., (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.
The Pan-African Research Network. (2022). Afrobarometer. https://www.afrobarometer.org/
Walden University. (2022). Skill builders. Interpreting the results from regression models. https://content.waldenu.edu/d1c00f22444bfb7cf79c9487accceada.html
Bottom of Form