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Academic Goals
Learning Goals for Psych 317 & 318: Intro to Probability & Statistics in Psychological Research
By the end of this course, students will be able to:1. Understand basic inferential statistical methods including:
(a) visual displays of data
(b) null hypothesis significance testing;
(c) confidence intervals for population parameters;
(d) effect size measures
2. Make appropriate choices among descriptive statistics to summarize psychological data in terms of location and spread, and, in the case of multiple variables, degree of association.
3. Understand and appreciate the logic behind hypothesis testing and the role of sampling distributions in the logic of hypothesis testing. Understand that statistical tests can prove nothing conclusively, and should be understood probabilistically. Appreciate the basic probability theory and the algebra of random variables that underlie inferential statistical thinking.
4. Make appropriate choices among inferential statistical methods to analyze data. Understand that the choice of the appropriate method depends on the type of variables under study (categorical, ordinal, measurements with interval properties), how many variables are under study, how many samples are obtained, what sorts of hypotheses are you interested in testing, how conservative/liberal one wishes to be with respect to Type I error and power.
5. Understand that the most commonly used statistical tests carry with them certain specific assumptions about the distributions being sampled from (equal variances, for example, in the independent groups t test and between subjects ANOVA techniques). Be aware that the selection of the appropriate statistical method is often based on considerations of Type I and Type II errors among alternative tests.
6. Make appropriate choices among inferential statistical methods in carrying out multiple tests within a data set. Understand that the choice of the appropriate multiple comparison method depends on the timing of the selection of tests (a priori, post hoc), the number of tests carried out, and the degree to which the tests are dependent on one another.
7. Distinguish between statistical significance and practical significance. Be able to use measures of effect size to compute power estimates for a study and to describe the size of the effect of an independent variable.
8. Use scientific writing to write about statistical methods selected and conclusions drawn from data.
9. Use either spreadsheet software or statistical software to create visual displays of data, compute basic quantitative summaries of data, and perform basic statistical tests.
