2 Semesters of Statistics!?
A course that most prospective doctoral students fear is Statistics. Previous blog posts have discussed tips on how to master statistics concepts like using MyStatLab; however, it is also suggested that students choose a statistics course that utilizes SPSS. SPSS is a statistical program that allows students and professionals to run calculations on t-tests (independent samples and dependent samples), analysis of variance, correlation, regression, and tests of assumptions (normality, homogeneity of variance, independence, linearity, and additivity) among other tasks.
I recommend that students take a course that uses SPSS software 22 or higher "throughout" the course. Students that are familiar with SPSS will have less trouble transitioning to doctoral level statistical analysis than those who are unfamiliar with SPSS. Also, taking two statistics courses prior to doctoral work is not a bad idea because an intro course usually teaches students how to calculate tests by hand (or without a program). Students should then take a second course that reviews statistical topics and utilizes SPSS. The point of taking two courses is to learn the concepts well.
Doctoral statistics heavily focuses on concepts like choosing which statistical test to use, interpreting graphs and charts, transforming data based on outcome of distribution, and knowing when to use parametric vs. nonparametric tests. All of these tasks require that students know introductory statistics concepts well like the names of tests, when such tests are used, how to interpret statistical significance based on the test used, Type I and Type II errors, confidence intervals, effect sizes, and power analysis to name a few items.
Many students begin statistics assuming they will solve equations and submit the answers; however, in doctoral studies, merely giving the value for a independent samples t-test and significant p value is no longer acceptable. Students must be able to complete the tasks discussed in the previous paragraph.
Thus, I recommend student take more than one course, ask questions in your courses, take good notes, obtain a statistics guide/manual from your university if available, and seek out online sources for additional help.
I recommend that students take a course that uses SPSS software 22 or higher "throughout" the course. Students that are familiar with SPSS will have less trouble transitioning to doctoral level statistical analysis than those who are unfamiliar with SPSS. Also, taking two statistics courses prior to doctoral work is not a bad idea because an intro course usually teaches students how to calculate tests by hand (or without a program). Students should then take a second course that reviews statistical topics and utilizes SPSS. The point of taking two courses is to learn the concepts well.
Doctoral statistics heavily focuses on concepts like choosing which statistical test to use, interpreting graphs and charts, transforming data based on outcome of distribution, and knowing when to use parametric vs. nonparametric tests. All of these tasks require that students know introductory statistics concepts well like the names of tests, when such tests are used, how to interpret statistical significance based on the test used, Type I and Type II errors, confidence intervals, effect sizes, and power analysis to name a few items.
Many students begin statistics assuming they will solve equations and submit the answers; however, in doctoral studies, merely giving the value for a independent samples t-test and significant p value is no longer acceptable. Students must be able to complete the tasks discussed in the previous paragraph.
Thus, I recommend student take more than one course, ask questions in your courses, take good notes, obtain a statistics guide/manual from your university if available, and seek out online sources for additional help.
