Visit the Appointment Scheduler to sign up for coaching and to self-schedule recorded and group sessions.
The Academic Success Center observes Pacific Time (PT) for scheduled coaching and live help hours.
Below is the current time on the ASC Scheduler clock:
Want to attend a group session? Reserve your seat today using the ASC Appointment Scheduler.
Please use the Academic Success Center Appointment Scheduler to reserve your seat to attend any of the available group sessions.
Review the Register tab of the Learn the ASC page for assistance with registering for scheduled coaching.
*All session times are scheduled in Pacific Time (PT).
Thursday 11:00 a.m.
Join the Charts & Variables group session to develop a greater understanding of variables in research. In this session, you will learn how to identify and define variables, describe the level of measurement of each variable, and construct various examples of these definitions. Additionally, you will discuss with the group how a variable’s level of measurement connects with the different descriptive and inferential statistics you can use, as well as the types of visual displays that are most appropriate.
Monday 2:00 p.m.
Join us to build your understanding of variables. What constitutes a variable? How are they operationalized? What is the importance of understanding the level of measurement? Join the Defining Variables group session for conversation and clarity around these statistical concepts.
Tuesday 3:00 p.m.
Are statistics mysterious to you? Are you feeling overwhelmed by the math? Join the Demystifying Statistics group session for conversation and clarity around common statistical terminology and analyses.
Thursday 4:00 p.m. beginning August 8
The new G*Power Group session is designed for graduate students who have questions about using the software to compute the a priori, post hoc, and compromise power of their statistical tests to obtain a sample size sufficient for generalization to the population.
Wednesday 6:00 p.m.
In this session, you will learn the steps of hypothesis testing and how to apply them to any statistical test. Topics covered include null/alternative hypothesis, the decision rule, alpha & beta, and type I & type II errors.
Sunday 4:00 p.m.
This group session will introduce you to the Statistical Package for the Social Sciences (SPSS) data analytic software. It is designed for the student who has little to no experience with SPSS. Do you know how to input data into SPSS or the differences between data view and variable view? Can you create graphs, tables, and charts in SPSS? Do you know how to import data into SPSS? In this session, you will learn these and other fundamental SPSS skills.
Friday 4:00 p.m.
This group session will introduce you to experimental, quasi-experimental, non-experimental, and causal-comparative research designs, including the description and general requirements for each design typology. During this group session, you will learn about the requirements for an experimental, quasi-experimental, or non-experimental research study. The information you learn during this interactive session will help you to make an informed design selection and fully understand why that selection is the most appropriate for your study.
Sunday 12:00 p.m.
Now presenting….(drum roll please)…..Reporting Results! Once the data has been collected and statistical tests have been run, it’s time to share those results with the reader. Whether your reader will be your instructor, dissertation committee, or readers of a journal, you want your results to be clear and organized. In this group session, we will identify the key components to include when reporting the results, explore how to apply those components across various statistical analysis designs, and practice applying these skills to your own work.
Thursday 5:00 p.m.
This group session will introduce you to using the SPSS software for univariate and factorial analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). This group is designed for the student who has experience with SPSS. Do you know how to test the assumptions of univariate and multivariate normality, homogeneity of variances and covariance matrices, and linearity? Or how to interpret the effect size, post hoc power, and multiple comparisons test? In this session, you will learn how to do these and other associated statistical techniques in SPSS.
Friday 5:00 p.m.
This group session will introduce you to using the SPSS software to run bivariate correlations, and simple/multiple linear regression analysis. This group is designed for the student who has experience with SPSS. Do you know how to test the assumptions of linearity, multicollinearity, independence, homoscedasticity, etc.? Or how to interpret the model summary, ANOVA, and coefficients tables? In this session, you will learn how to do these and other associated statistical techniques in SPSS.
Sunday 3:00 p.m.
The SPSS: Open Topic group session is designed to provide graduate-level students with information and hands-on experience with SPSS topics that are not covered in the other weekly SPSS group sessions (i.e., Introduction to SPSS, t-tests, ANOVA/MANOVA, or Correlation/linear regression).
Tuesday 5:00 p.m.
This group session will introduce you to using the SPSS software to run single sample, independent samples, and paired-samples t-tests. This group is designed for the student who has experience with SPSS and can run basic descriptive statistical summaries, tables, graphs, etc. Do you know how to test the assumptions of normality and equality (homogeneity) of variances? Or how to interpret confidence intervals, equality of variances, equality of means, or means differences tables? In this session, you will learn how to do these and other associated statistical techniques in SPSS.
Friday 12:00 p.m.
Identifying the right statistical test does not have to be frustrating. Join the Which Stats Test group session to learn the thought process behind test identification and how to apply this process to pick the right test every time. Students are encouraged to join with an understanding of basic variable concepts (i.e., types of variables and levels of measurement). To brush up on these concepts, consider attending at least one of these group sessions first: Charts & Variables, Demystifying Statistics, and Defining Variables.