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## Research Methods, Week 13 notes

by: Clarissa Hinshaw

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# Research Methods, Week 13 notes Psych 305

Marketplace > Northern Illinois University > Psychlogy > Psych 305 > Research Methods Week 13 notes
Clarissa Hinshaw
NIU
GPA 3.5

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## About this Document

Notes for chapter 13
COURSE
Research Methods
PROF.
Keith Millis
TYPE
Class Notes
PAGES
2
WORDS
CONCEPTS
Psychology, research methods
KARMA
25 ?

## Popular in Psychlogy

This 2 page Class Notes was uploaded by Clarissa Hinshaw on Sunday April 24, 2016. The Class Notes belongs to Psych 305 at Northern Illinois University taught by Keith Millis in Winter 2016. Since its upload, it has received 8 views. For similar materials see Research Methods in Psychlogy at Northern Illinois University.

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Date Created: 04/24/16
Chapter 13 Understanding Research Results: Statistical Inference  Inferential Statistics: using the results to predict what would happen if the study was  replicated.   Null hypothesis: hypothesis stating no relationship between 2 or more variables.   Research hypothesis: the hypothesis stating a relationship between 2 or more variables.   If the null hypothesis is rejected, the research hypothesis is considered accepted.   Statistical significance: the likelihood of the same results occurring in the general  population, rather than by chance.   Probability: the likelihood of something happening.  The alpha level is the minimum amount of probability required to obtain significant  results.   Binomial distributions and sampling distributions are examples of calculating probability.  Degrees of freedom: df, the sample size of a t­test.   Using a 1 or 2 tailed test depends on whether a direction or difference is mentioned  between the groups.  F­test: aka analysis of variance, the test used when calculating anova.   Systematic variance: deviation from the mean score.  Error variance: deviation of individual scores from their group means.   Goals of a statistical test:  o Deciding reliability o Calculate confidence interval o Results are more significant with a larger sample size. o Large effect=more significant results.   Type 1 error: rejecting a true hypothesis. Ex: doing a c­section on a mother who doesn’t  need it.   Type II error: accepting a false hypothesis. Ex: not doing a C­section when it is needed.   Power: a sample size possible to reject the null hypothesis.

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