Symbols Used in an APAStyle Regression Table
Source

B

SE B

β

t

p

Variable 1

1.57

0.23

.23

2.39

.020

Variable 2

1.26

2.26

.05

0.58

.560

Variable 3

1.65

0.17

.28

2.92

.005

Aligning theoretical framework, gathering articles, synthesizing gaps, articulating a clear methodology and data plan, and writing about the theoretical and practical implications of your research are part of our comprehensive dissertation editing services.
There are five symbols that easily confuse students in a regression table: the unstandardized beta (B), the standard error for the unstandardized beta (SE B), the standardized beta (β), the t test statistic (t), and the probability value (p). Typically, the only two values examined are the Band the p. However, all of them are useful to know.
The first symbol is the unstandardized beta (B). This value represents the slope of the line between the predictor variable and the dependent variable. So for Variable 1, this would mean that for every one unit increase in Variable 1, the dependent variable increases by 1.57 units. Also similarly, for Variable 3, for every one unit increase in Variable 3, the dependent variable decreases by 1.65 units.
The next symbol is the standard error for the unstandardized beta (SE B). This value is similar to the standard deviation for a mean. The larger the number, the more spread out the points are from the regression line. The more spread out the numbers are, the less likely that significance will be found.
The third symbol is the standardized beta (β). This works very similarly to a correlation coefficient. It will range from 0 to 1 or 0 to 1, depending on the direction of the relationship. The closer the value is to 1 or 1, the stronger the relationship. With this symbol, you can actually compare the variables to see which had the strongest relationship with the dependent variable, since all of them are on the 0 to 1 scale. In the table above, Variable 3 had the strongest relationship.
The fourth symbol is the ttest statistic (t). This is the test statistic calculated for the individual predictor variable. This is used to calculate the p value.
The last symbol is the probability level (p). This tells whether or not an individual variable significantly predicts the dependent variable. You can have a significant model, but a nonsignificant predictor variable, as shown with Variable 2. Typically, if the p value is below .050, the value is considered significant.
Statistics Solutions can assist with your quantitative analysis by assisting you to develop your methodology and results chapters. The services that we offer include:
Edit your research questions and null/alternative hypotheses
Write your data analysis plan; specify specific statistics to address the research questions, the assumptions of the statistics, and justify why they are the appropriate statistics; provide references
Justify your sample size/power analysis, provide references
Explain your data analysis plan to you so you are comfortable and confident
Two hours of additional support with your statistician
Quantitative Results Section (Descriptive Statistics, Bivariate and Multivariate Analyses, Structural Equation Modeling, Path analysis, HLM, Cluster Analysis)
Clean and code dataset
Conduct descriptive statistics (i.e., mean, standard deviation, frequency and percent, as appropriate)
Conduct analyses to examine each of your research questions
Writeup results
Provide APA 6^{th} edition tables and figures
Explain chapter 4 findings
Ongoing support for entire results chapter statistics
Please call 7274424290 to request a quote based on the specifics of your research, schedule using the calendar on t his page, or email [email protected]