Fichas
Quiz 1
Fichas del conjunto (63)
- 1why focus on stats?you cannot understand what physiologists do or ever do it yourself, w/o knowledge of stats.
- 2why are stats essential for physchological science ?psychologists goal is to provide objective answers to questions about human behavior
- 3why should we love stats ?because being able to answer questions objectively is a great thing especially when questions are controversial
- 4stats allow us to______and______ dataorganize and interpret
- 5why must data be organized ?w/o organization , data are just a meaningless bunch of numbers and can't be used to answer interesting questions
- 6calculating averages is a_________ techniquestatistical
- 7descriptive statisticsdescribing the behavior of the specific people in a specific sample
- 8interpretationfiguring out what data mean, drawing conclusions from data interpretation
- 9psychologists care about what the data mean for people in_______the population
- 10psychologists want to know about ________, but are forced to study _______ because it's impossible to study every single person in a popultion-populations
-samples - 11using __________ _____ to look at the behavior of people in a sample does not , by itself tell us anything about people in the populationdescriptive stats
- 12inferential statisticsused to figure if a difference in a sample is good evidence that the same difference would exist for people in general
- 13inferential statisticslet us infer something about a population based on a sample
- 14together _________ and ________ ____ allow us to answer questions about populations by studying samplesdescriptive and inferential statistics
- 15psychological science requires ______creativity
- 16turning complex behavior into numerical facts requires a great deal of ______creativity
- 17variablea characteristic of a person that can have at least 2 possible values
- 18for variables the values are either _______ or ________-numbers
-categories - 19aa persons particular value is the persons _________score
- 20numeric valuesvariables in which values are numbers
- 21categorical valuesvariables in which values are categories
- 22its important to recognize the difference between categorical and numeric values becausethe kinds of variable you have determines the statistical tools you can use with the variables
- 233 types of investigation where data come from1. observational studies
2.experiements
3.quasi experiments - 24observational studies-can only show that when people differ on an explanatory variable , they may also differ on a response variable
* there may be a third variable that causes the difference in response variables - 25explanatory variablea variable we think might partially explain behavior ( sometimes called independent variable)
- 26response variablea variable we want to measure ( sometimes called dependent variable)
- 27observational studies limitation:don't provide evidence if causation , they can't reveal whether the explanatory variable caused a difference in the response variable
- 28observational studies are often presented in the press and elsewhere as if they provide evidence of _________causation
- 29experimentstype of investigation that can provide evidence of causation
- 30experiment features:- shared with observational studies
but
-involve randomly assign sample members to particular values (or diff. conditions)
- no worry/ less worry about third variable problem - 31quasi- experiements-sometimes random assignment of subjects to levels of the explanatory variable is difficult, if not impossible
-researchers might compare 2 groups
that naturally differ - 32reseachers in quasi experiments think they are observing a marker for a ______________ and then consider that ____________ to be the explanatory variablethird variable
- 33in observational studies , the observed variable is considered to be the ____________________explanatory variable
- 34quasi experiments have all the same features as observational studies and do not have _________random assignment
- 35different values of an explanatory variable are sometimes calledthe different levels of the variable
- 36randomness is important in 2 steps of data collection-selection of study participants
-assignment of participants - 37third variable problemthe problem that can make it hard to argue that explanatory variables cause differences in response variables
- 38why select participants randomly ?we want samples to represent the population
- 39random selection produces arepresentative sample
- 40why assign participants to conditions randomly ?-avoid bias
-produces groups that on average are similar to each other
- it's vital that groups in an experiment are similar - 41dependent measure =response variable
- 422 response variables-categorical variables
-numerical variables - 43what are inferential stats for ?deciding if a difference that occurs in a sample is good evidence that the same difference would occur in the population
- 44why are there so many different inferential statistical tests ?because investigations can be set up in different ways and you need a specific test for each specific set up
- 45different set ups are calleddifferent experimental designs
- 46Paired T-Test- there is 1 and only 1 group of SS
-each subject was exposed to 2 and only 2 levels of explanatory variables - 47Two Sample T-Test- 2 and only 2 groups of subjects
-each subject was expose to 1 and only 1 level of the explanatory variable - 48One Way ANOVA (analysis of variance )-3 or more groups of subjects
-each subject was exposed to 1 and only 1 level of explanatory variable - 49Random samplingpsychologists achieve representative samples
- 50random assignmentpsychologists create groups of subjects that are similar to each other
- 51Chi-square Testresponse variable is categoical
- 52Factorial ANOVA ( analysis of variance)2 (or more) explanatory variables
- 53inferential statistical tests are tools forinterpreting data
- 54we want to organize data to show thedistributions of a variable
- 55variables are shown inbar graphs= categorical
histograms= numeric - 56bar graphs showthe different values the variable can have
- 57histograms showthe different distributions of the numeric variable
- 581 peak in histograms =unimodal
- 592 (or more peaks ) in histograms =-bimodal (2)
-multimodal (>2) - 60idealized depictionbell curve/ bell shape
- 61midpoint=between lowest value and highest value in a sample
- 62If frequencies skew to the left=negatively skewed
- 63if frequencies skew to the right=positively skewed