Teacher Perceptions of Principal Support and Collective Responsibility Affect Self-efficacy7/25/2018 Variables The purpose of this multiple regression test is to examine whether math teachers’ perceptions of collective responsibility and principal support, the independent variables measured as interval-ratio, affect math teacher self-efficacy, the dependent variable measured as interval-ratio. Each variable data was taken from the High School Longitudinal Study dataset (National Center for Educational Statistics, 2009). Since I am using two independent variables to examine how it affects one dependent variable, multiple regression serves as the best model to complete such task (Frankfort-Nachmias & Leon-Guerrero, 2018). Nonetheless, the multiple regression test reveals a statistically significant relationship between the two independent variables and the dependent variable. Model and ANOVA The model summary reveals an R-value of .21, indicating the Pearson Correlation Coefficient is a slight positive correlation between math teachers’ perceptions of principal support and collective responsibility against math teaching self-efficacy. Also, the Adjusted R Square value of .45, indicates 45% of math teachers’ self-efficacy is affected by their perceptions of principal support and collective responsibility (Laureate Education, 2016). The ANOVA test reveals an F value of 331.63 at a significance of .000, well below the conventional .05 alpha level, therefore, rejecting the null that math teachers’ self-efficacy is not affected by their perceptions of principal support and collective responsibility.
Coefficients The Unstandardized Coefficients Beta value for math teacher’s perceptions of principal support is .062, meaning for one unit increase in perceptions of principal support, math teacher’s self-efficacy will increase by .062. A one unit increase in math teacher’s perceptions of collective responsibility, math teacher’s self-efficacy will increase by .165. Lastly, the significance of each independent variable is .000, indicating a rejection of the null that there is no relationship between teacher’s perceptions of principal support and collective responsibility against math teacher’s self-efficacy (Laureate Education, 2016). Therefore, we can conclude that teacher perceptions of principal support and collective responsibility do affect their ability to deliver effective instruction.
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SPSS was used to analyze the data from the 2014 General Social Survey data set which reveals both hours watching TV and time spent on the internet during the week affect your socioeconomic status. The Model Summary of the Multiple Linear Regression tests reveals that 40% of socioeconomic statuses are explained by the two independent variables; hours spent watching TV and time spent on the internet. The ANOVA test has a significance of .000, below the .05 alpha level indicating the rejection of the null that there is no relationship between variables. Nonetheless, analyzing the unstandardized coefficients reveals for every unit increase of hours per day watching TV, SES will decrease by 1.668 units. For every unit increase in internet hours per week, SES will increase by .130 units. The significance of each independent variable is statistically significant at the .01 alpha level and are statistically significant predictors of SES. Thus, in laymen terms, the more you watch TV, the less money you will make and the more time you spend on the internet, the more money you will make. However, there are multiple influences that affect hours spent on the internet, some beneficial to income, some not.
The purpose of this bivariate correlation test is to examine whether math teachers’ years of service are correlated with students’ mathematics self-efficacy using the High School Longitudinal study data (National Center for Educational Statistics, 2009). The correlation test is used to determine the level of association between the two variables and the strength of the association (Frankfort-Nachmias & Leon-Guerrero, 2018). The results of the test indicate a p-value of .047, just under the conventional .05 threshold, therefore rejecting the null that there is not a statistically significant relationship between the two variables. Because of the rejection of the null, a linear regression test can be utilized to determine the strength of the relationship. Linear Regression Test The Linear Regression test reveals that for every year of experience a math teacher completes, students’ mathematics self-efficacy increases by .2%. Also, The standardized coefficients value is computed at a level of .017, which indicates a very slight positive correlation between the two variables as it is just above 0 (Frankfort-Nachmias & Leon-Guerrero, 2018). Such statistical data can help provide social change for educators across the globe by helping teachers remain in the field of teaching mathematics. Further, such information could entice further research in examining teacher confidence and ability to deliver seamless instruction. References
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: SAGE Publications, Inc. National Center for Educational Statistics. (2009). High school longitudinal study [data file]. |
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