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Lecture 11

LECTURE 11 Research Methods

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PSYC 2030
Krista Phillips

Exam: 100 MC  150 mins 15 items/ chapter 15 lecture items 15 items  hypothetical research scenarios HB + Student ID 5 chapters  on syllabus NOT CHAPTER 10 Example of the application question: Dr. X is interested in whether or not there are differences between 10 yr olds and 5 year olds... described test , way test is administered. What is a likely confound? What might the sources of those differences be? R squared/ omega squared. LECTURE 11 OUTLINE 1. The logic of inferential statistics Inferential statistics rests on sampling theory. Chance factors that are inherent in forming samples will always affect your results. Your results therefore must be interpreted in that light. The purpose of inferential statistics: looking for accurate reading to illuminate factors of chance(sampling variation). Will such a difference change with the retraction of sampling variation. Allows us to make statements about true differences between groups. Comparison of 2 Methods of Math Training Group 1 Group 2 (Novel) (Traditional) Mean = 80% 75% Math Textbooks for boys. Is it a significant difference? Always remember: a significant difference can be obtained in many ways. 2. Four factors which can produce significant differences between groups. 4 Common Factors Can Produce a Significant Difference: 1) Chance  more clever boys in group 1 and not group 2 2) Operation of the Independent Variable  training is actually effective. 3) Error  scoring error, calculation error. 4) Fraud  pressure on graduate students to publish something. Duplication of observations in favour of hypothesis. 3. Sampling theory. Significance tests don’t tell us where it came from. 1 of the 4 above. Significance testing determines the make a
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