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PSY 101: Research Method II & III (Quantitative), week 2 notes

by: Alvin Notetaker

PSY 101: Research Method II & III (Quantitative), week 2 notes PSY 101

Marketplace > Arizona State University > Psychlogy > PSY 101 > PSY 101 Research Method II III Quantitative week 2 notes
Alvin Notetaker
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About this Document

The rest of the Research methods.
Introduction to Psychology
Class Notes
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This 5 page Class Notes was uploaded by Alvin Notetaker on Saturday January 23, 2016. The Class Notes belongs to PSY 101 at Arizona State University taught by Mae in Winter2014. Since its upload, it has received 30 views. For similar materials see Introduction to Psychology in Psychlogy at Arizona State University.


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Date Created: 01/23/16
Research Method II & III (Quantitative)    Descriptive Research:  ● When?  ○ To learn descriptive information about a group or event.  ● How?  ○ Records  ○ Surveys  ○ Interviews  ○ Observations  ● Statistical Analysis of Descriptive Data  ○ Mean (average)  ○ Median (after ordering the data, the middle is the median)  ○ Mode (most frequent)  ○ Percentage (use for categories)    Correlational Research:  ● When?  ○ To investigate possible relationship  ● How?  ○ Since this research is looking for a relationship between two factors, just measure  both factors.  ● Limitation?  ○ Does not tell which way the arrow is pointing (The factor that causes the effect.)  ● Example:  Is there a relationship between aggressive TV & aggressive behavior  Yes, but which way?    Correlation Coefficient = r:  ● Range of r?  ○ ­1.00 to 1.00  ● How to interpret r?  ○ If there is a relationship  ○ Positive or negative?  ○ The strength of the relationship?  ● Positive relationship:  ○ ↑↑or ↓↓  ● Negative relationship:  ○ ↑↓or ↓↑      ______________________________________________________________________________  −1.00 →  −0.60 = Strong negative relationship  −0.59 →  −0.40  = Moderate negative relationship  −0.39 →  −0.20 = Small negative relationship  −0.19 →  +0.19 = No relationship  +0.20 →  +0.39 = Small positive relationship  +0.40 →  +0.59 = Moderate positive relationship  +0.60 →  +1.00 = Strong positive relationship  ______________________________________________________________________________  (Note any number above or below the r range is considernot existin, so the relationshave  to be between the range.)  ● Example:  [Name] found the relationship between “x” and “y” to be +0.25.  1. There is a relationship between “x” and “y”  2. The relationship is small positive relationship  [Name] found the relationship between “z” and “k” to be ­0.67.  1. There is a relationship between “z” and “k”  2. The relationship is ​trong negative relationship  [Name] found the relationship between “p” and “q” to be +3.09  1. This does not exist  {Name] found the relationship between “o” and “r” to be ­0.06  1. There is ​o relationship    Experiments:  ● When?  ○ When you wish to draw cause and effect conclusions  ● How?  ○ Manipulate a variable under controlled condition  ● Independent Variables (IVs):  ○ The one the experiment manipulates (or varies)  ● Dependent Variable (DVs):  ○ The outcome thought to be affected by the independent variable.  ● Groups:  ○ Experimental ­ gets the IV  ○ Controlled ­ nothing  ● Example:  A higher education leads to higher income.  1. IV ­ Higher education  2. DV ­ higher income  3. Experiment group ­ people get ​igher education  4. Controlled group ­ people get​ormal​ education    Relaxation can be heightened with biofeedback.  1. IV ­ Biofeedback  2. DV ­ Relaxation  3. Experimental group ­ people who ​gets biofeedback  4. Controlled group ­ people who ​on’t get biofeedback    Bad weather causes depression.  1. IV ­ Bad weather  2. DV ­ Depression  3. Experimental group ­ People who ​experience​ bad weather  4. Controlled group ­ people who don’t experience​ bad weather    More than one variable for IV and DV:  ● Why want more than one DV in the experiment?  ○ Efficiency and “why not?”  ● Why want more than one IV in the experiment?  ○ Look for interaction        Nitrates  N                 Y  ­  ↑      Viagra  N                 Y  ­  ↑        Nitrates        N  Y  Viagra  N  ­  ↑    Y  ↑  ↓     The cell with the arrow pointing down is called, ​interaction cell.    ● Example:  Wonder if smoking causes lung cancer even if there is a healthy diet.  1. IV ­ Smoking and healthy diet  2. DV ­ Lung cancer   3. Experimental group ­ people who smokes a lot with various amount of healthy  diet  4. Controlled group ­ people who smoke less often or don’t smoke with various  amount of healthy diet  ● True Experiment criteria:  ○ Manipulate ​ the IV while controlling everything else.  ○ Randomly​  assign participants into group.    More tricks/Keywords  ● Experiments:  ○ Cause, lead to, results in, affects, reduces, increases, ect.  ● Correlational research:  ○ Relationships, related, linked, associated  ● Descriptive research:  ○ Describe, demographics, composition  ● Qualitative Survey:  ○ Opinions, attitudes  ● Natural Observation:  ○ Public behavior  ● Case Study:  ○ Unusual or infrequent phenomena    Significance Testing of Comparative Data:  ● Compare 2 or more group  ● Significantly different or just due to chance?  ● What’s in a p­value?  ○ Group means  ○ Group variability  ○ n (number of subjects per group)  ○ N (total number of subjects in experiment)  ● How to interpret a p­value?  ○ p = probability due to chance (you want the value to be ​ small​)  ○ p­values  i. p < 0.05 = significantly different  ii. 0.05 < p < 0.10 = marginally significant(withhold judgment and collect  more data.)  iii. p > 0.10 = not significant    Bloopers (& how to protect from them)  ● Sampling bias​ : Consistent error that arises due to the sample selection.  ● Confounding variables​ : Factors other than the independent variable that may cause a  result.  ● Placebo effects​ : A phenomenon in which the participants’ expectations, rather than an  actual treatment, produce an outcome.  ● Experimenter bias​ : The influence of the experimenter’s expectations on the outcome of  research  ● Social desirability effects​ : People respond to questioning in ways that make them seem  more favorable or appealing to others 


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