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## Intro to Research Chapter 5 Week 3 Lecture

by: Kim Notetaker

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# Intro to Research Chapter 5 Week 3 Lecture

Marketplace > Armstrong State University > > Intro to Research Chapter 5 Week 3 Lecture
Kim Notetaker

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These notes are a summary of Chapter 5. These notes pertain to what will be on our exam.
COURSE
Intro to Research Methods
PROF.
TYPE
Class Notes
PAGES
5
WORDS
CONCEPTS
PSYC, research, notes
KARMA
25 ?

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Date Created: 09/30/16
Chapter 5 Scales of measurement (NOIR)  Nominal: values are just labels and categories. o An example would be, are you happy? Yes or no.  Ordinal Scale: the rank ordering and the amount of space between the ratings doesn’t matter.  Interval: the equal differences between the numbers reflects the equal differences on the dimension being measured. This has NO true zero or absolute zer0. o An example would be how happy you are on a scale of 1-7. 1 being the least happy and 7 being the most.  Ratio: the interval scales plus a ‘true zero.’ This is a good measure of behavior. o An example would be asking how many times did you feel happy today? How do we know if our measures are good?  Validity: the degree to which a measure is an accurate representation of the construct we want to measure.  Reliability: the consistency, stability or dependability of a measure. Correlation Refresher  We typically measure reliability with correlation.  Correlations Co-efficient (r): measures the strength and direction of the association between 2 variables.  Strength: how well can you predict one thing by knowing about the other? (ranges from 0 to +/- 1) o 0 = no correlation o .1 - .3 = small correlation o .3 - .5 = medium correlation o .5 or larger = large correlation  Direction: as one variable goes up does the other variable go up or down?  Positive Correlation: all the variable either go up or down at the same time.  Negative Correlation: one variable goes up while the other goes down. 3 assessments of reliability  Test re-test Reliability: the consistency of the results over time.  Relevant to ALL types of measures (self-report, observational and psychological) BUT only when the construct is stable.  It measures more than once and calculates the correlation between the scores. o An example would be trait level happiness.  Interrater Reliability: consistency over observers.  Relevant to observational measures (video/Audio).  Ask more than one person to rate the observations on a measure of interest, correlate the two sets of rating. o An example would be observed happiness.  Internal Reliability: consistency across scale items. 2  Relevant to self-report measures that have multiple items assessing the same construct. o An example would be the Subjective Happiness Scales by Lyubomirsky.  Typically assessed with a type of correlation: Cronbach’s alpha. o Step 1: Compute all possible connections between the items. (item 1 with item 2 and so forth.) o Step 2: Take the average of these correlations. o Step 3: Fancy math with the average of the correlation and the number of items = Cronbach’s alpha. o You want it to be greater than .70. 5 Types of Construct Validity  Construct Validity: How well did the researcher operationalize each variable?  Face Validity: Does the measure seem like a plausible one, given the construct of interest? o Entirely subjective. (don’t over think this one!!) o Usually determined by experts.  Content Validity: Does the measure capture all parts of the construct of interest? o Entirely subjective. o Usually determined by experts.  Criterion Validity: Is the measure related to relevant objective outcomes? 3  Correlation between scores on your measure and concrete objective outcomes (no other subjective outcomes). o An example question to ask would be: What objective outcomes should happiness be related to?  Another option is the know groups paradigm: this is when you take groups you know to be different and give them the measures.  Convergent Validity: Is the measure related to other measures that assess similar constructs?  Correlations between scores on your measure and scores on other subjective related measures. o A question to ask is: What other measures should happiness be related to?  Satisfaction with life scale (Diener)  Positive and negative affect schedule (Watson and Clark)  Discriminant Validity: Is the measure NOT related to other measures that assess different constructs? o NOTE: Looking for weak correlations not negative ones. o Only important for constructs that are similar but distinct. 4 5

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