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Chapter 7 RM

QuestionAnswer
Experimental manipulation when experimenter treats group differntly according to IV levels, Random assignment to Ps to conditions
Correlation No mainuplated variable, no independent variable
Simple Experiement IV is manipulated, DV is measured
Basic Experiment 2 levels of IV, experimental group, control comparison group
Control over extraneous variables randomizing, matching
* Casual relationship between IV and DV can be established
Methods to contol confunding variables Design to experiemtn, randomization, matching, control of partcipants effects/ experimenter effects, manipulation check
Randomization most important
Randomization selcection Representativenesss, eliminates systematic bias, increase external validity
Random assignment to conditions equal distribution of partcipant characteristics to conditions, increases internal validity, more important than random selection
Value of assignment- manipulating the treatment random assignment makes the IV the obly systematic difference between groups, no random assignment= no experiment
Control procedures increases sensitivity of an experiment, eliminates that variable are being controlled as a cofund
Holding variables construct creates a more homogenous sample
Matching by building extraneous variables into the research desing to compare two populations
Building extraneius variables into the design excellent for acheiving control and increasing sensitivity, matching
Matching by Yoked Control controls the possible influence of the time relationsjip between an event and behavior
Control of parcipant effect demand characteristics, double blind placebo model, deception, manipulation check
Control of experimenter effects practice beig consistent, run all conditions at the same time, automation, recorded instructions control recording errors- procedural reliability blind to condition control of exoeriments attributes error- blind counter balance
Remember that Simple experiment is a simple way to establish internal validity, independent random assignment = cornerstone, control partcipant diffrence through matching, hypthesis testing to determine if the differences are relaiable. Type 1 vs type 2 error- t-test
Reporting the T-Test results Include statistical test, degress of freedom, probability of significance level- if significance level is below .05 you can reject the null hypthesis. if above .05 you retain the null hypthesis
Results- inferential statistics means, standard deviation and standard erro for each measure for each group report the inferential statistic results, explain results, give statisical evidnece, develop and claify the point use impartial scientific reporting
Assumptions of the T-Test observations are indenpendent, internal or ratio, underlying distributions are normally distributed both groups distributions have the same variance
Analyzing the results of the simple experiment decide on significance level before doing experiment- is the difference not due to change, if not statistically signicant- conclude nothing, if statisically significant- effect probably reliable but not neccessarily large/important
Power- reducing type II error reduce the effect of random error, standarize procedures and use relaible measures, code data carefully
Statisfically significant results- declaring that the treatment has an effect not necesairlily large control group rule out- placebo effect, experiment bias and other confunding variables
Statisical question is the observed mean difference greather than what is expected based on the assumed diffrence of zero
Null Hypotheis the treatment doesnt have an affect
Experimental hypthesis treatment has an effect IV-> DV
Simple Experiment Overview- errors in determing weather results are statiscally significant statistic and the design of the simple experiment, nonstatistical considerations in the design of the simple experiment, analyzing data from the simple experiement
Created by: gbills16
 

 



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