exam 2 Flashcards by Teresa Nguyen

what are ways to get data?

observations, archival data, and cases studies

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what are the advantages of getting data for frequency claims?

inexpensive
investigate naturally occurring stuff, manipulation not allowed
convenient
flexible

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type of research that relies on one of your sensations to gather data
systematic bc you researched about this and coded what to look for
subjective research

observational research

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what is the purpose of observational research?

describes naturally occurring behaviors

as a measurement tool/assesses effects of the IV

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type of observation where you watch subjects in a natural setting;you go to person’s natural environment
unobstrusive

naturalistic/field observations

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type of observation where researcher becomes part of the environment they are studying
risks that the researcher will influence the study

participants’ observations

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type of observation where subjects come to you/your office/your lab
you manipulate the IV

systematic/controlled observations

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types of observations

naturalistic/field observations
participants’ observations
systematic/controlled observations

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method of coding behaviors where you count how many times stuff happens
determines the length of time
has distinct responses
-when it started and when it stops

frequency method

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method of coding behaviors where you determine how long the thing lasts
onset and termination
long length of time or infrequent responses
-deciding when the behavior started and when it stops

duration method

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method of coding behavior where you determine when the behavior did happen during this specific time interval
yes or no decisions
you have to decide on length of interval
number of intervals in which the behavior occurred

interval method

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method of coding behavior where man-made errors are non-existent
can record data accurately
most reliable type of method
ex: video and computer

technology

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techniques of coding behavior

frequency method
duration method
interval method
technology

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potential threat to construct validity, in which observers record what they want to see or expect to see, rather than what is really happening

observer bias

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sets of numbers, sets of scores

data sets

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the difference between numbers

variability

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goal of looking for variability

looking for variability between participants and between groups

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variable that explains what this is, things you didn’t anticipate/control; might influence study but you can’t control

extraneous variables

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effect that is due to independent variables vs what is luck/chance

effect of independent variables

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1 person or organization

participant

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in case studies, in order to collect data, you use interviews, psych-tests, medical records, school records, finances

data collection

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what is the two-fold purpose of a case study?

1) looking for a pattern

2) looking to confirm patterns in prev cases

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what’s the problem of case study?

does not talk about your average people (not visually applicable)

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you use archives/libraries to research info/data

archival research

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data collection drawback?

the sources to collect data is already there, but you need to find the data

type of archival research that has polling purposes

statistical records

type of archival research that has stored data

survey archives

type of archival research that already has documents of past research/studies stored

written and mass communication

types of archival research

statistical records survey archives written and mass communication

problem of archival research

we do not know the procedures of how the research collected its data

the procedure you followed in conducting your study | contains: design, participants, materials, procedure

method

things to talk about in the participants' section of research paper

``` demographics selection group assignment incentives generalization ```

things to talk about materials and procedures

step by step description specialized equipment if needed, have subsections

purpose of appendix

appropriate for presenting full text of research materials, when such info is too long to present in the method section

how to label more than one appendix

Appendix A, Appendix B, and so on

tools for critical thinking; set of tools that help researchers make sense of the data they've collected in the study

stats

why do we use stats?

bc stats is objective which clarifies communication

allows us to organize and summarize the props of a set of data; describe a set of scores

descriptive stats

type of descriptive stats that summarizes the performance of that group into one rep. number uses mean, median, and mode any time we get mean, we get std dev. too

central tendency

type of descriptive stat that tells us how spread out the scores are uses min and max, range, and variance and std dev,

measures of variability

type of descriptive stat that looks at the visual rep of data uses graphs, charts, etc

form

types of descriptive stats

central tendency measures of variability form

measure of central tendency where you take the average data

mean

measure of central tendency where you find the score in the middle chosen as a stat of choice bc it's not affected by extreme scores

median

measure of central tendency where you count how often each score appears/the most frequent this is a nominal scale bc it's the most useful and categorical

mode

high score- low score | is influenced by extremes scores

range

the avg squared dev from the mean

variance

avg distance of the scores from the mean

standard dev

what do high sd and low sd mean about your data?

high sd= scores are spread out | low sd= scores are similar (the closer it is to 0 the better)

``` a diagram consisting of rectangles whose area is proportional to the frequency of a variable and whose width is equal to the class interval. kinda like a bar graph ```

histogram

graph tilted to a diff direction

skewed curve

typed of skewed curves

skewed right | skewed left

what does a skewed left graph mean?

more lower scores

shape of two frequent scores on graph

bimodal

normal if you get a perfect distribution/curve, it means you get an equeal amount of scores mean and median would be equal it unimodal

bell-shaped

shape of one frequent score on graph

unimodal

taking two quantitative pieces of data and see where they intersect used for correlation stats

scatterplot

a set of techniques that use chance and probability to help researchers make decisions about what their data means and what inferences they can make from it -deduce something; concluded

inferential stats

estimates about what everyone else would do on your sample

sample estimates pop.

our task in how variability influences results

stats will allow us to separate our IV from luck

what is the analogy of radio

iv=finding the radio channel random variable=radio static to control this is by finding the control to prevent random variables

what allows us to tweak the signal in the radio analogy the likelihood of the occurrence of some event of outcome we want rare chance, no probability basis of whether we accept or reject the null hypothesis

probability theour

reasoning from specific results to broad generalizations about the world this would be in the discussion section

inductive reasoning

what don't you say in papers (proof or probability?)

proof

correctly reject a false null hypothesis

power

more severe | when you reject the null hypothesis even though it's true

type 1 error

when you accept null hypothesis even though it's false

type 2 error

use quantitative variables ordinal, interval, and ratio scales correlation test and analysis of variance (ANOVA)

parametric

qualitative variables nominal scales or ordinal scale chi-square

non parametric

order of analysis

descriptive stats | inferential stats

stats that has all quantitative variables if there's a pos correlation, that means there's a direct relationship r

pearson's correlation

stats that has all qualitative variables statistic used to study relational research and way to investigate association claims measures how far the observed value of each cell is from the expected value in each cell x2

chi-square

stats that has quantitative and qualitative causal claims 2+ groups F

ANOVA

there will be a relationship, trend, or mean diff

research hypothesis

establishing significance

p<0.5

number of scores free to vary once mean is known | particular to stat

degrees of freedom

a way to take 2 categorical variables and see how they can be combined

contingency table

how to give statistical presentation

inferential stats | descriptive stats

clrifies and compresses data supplements text, doesn't repeat text offers refs but you refer it in the result section

tablels

comes after tables | contains graphs, pics, and drawings

figures

deductive reasoning and inductive reasoning evaulates and interprets results future studies

discussion

it is your page 2 description 150-200 words

abstract

Has Interviews, Questionnaires, Instruments, and Inventories Used for Descriptive Research/Frequency Claims used to examine attitudes, opinions, and beliefs

survey

``` list of questions advantages: Inexpensive Large Sample Geographic Diversity Data Analysis ```

questionnaire

concerns about questionnaires

``` consider position effects (people skip questions at end of survey) response rate (how many surveys are returned to you) ```

questionnaires that many people have used | someone created this for their study and now others use this as well

instruments and inventories

types of instruments and inventories

personality inventories IQ tests anxiety assessment

direct verbal communication (on phone or in person) money and time- travel to meet in person has flexibility- you can modify questions as you go along

interviews

what makes a successful interview

good rapport | standardization of testing

short answer/essay | they share thoughts with you on that topic

open-ended questions

you supply answers and they have to pick one answer | ex: multiple choice, true false, yes no, male female

forced choice

people are presented with a statement and are asked to use a rating scale to indicate their degree of agreement On a scale of 1-5, rate which you agree with. 1=strongly disagree, 2=disagree, 3=neutral, 4=agree, 5=strongly agree Ordinal Scale can be Qualitative or Quantitative

likert scale

respondents are asked to rate a target object using a numeric scale that is anchored with adjectives

semantic differential format

how do you create rapport

filter questions | funnel questions

whats the problem with surveys

when people know you are doing a research study, they change behavior/answers

lie to you in a study to make themselves look good (politically correct)

social desirability/evaluation apprehensive

helps you with your study, finds out what resuts you want and then just gives you what you want

response acquiescence/good subjects

want to screw up your study results

response deviation/negative subjects

volunteer prob/self-selection sampling

volunteers are smarter, people-pleasers, and are well-adjusted

questions loaded with emotion

loaded questions

pulling people to answer a certain way

leading questions

asking 2 questions in one

double barreled questions

if you want to say yes, you disagree with the questions

double negatives

agree/disagree to a list of things bc of a pattern

yea saying and nay saying

every individual that has the chars you are interested in

population

smaller group that is drawn from the pop; asked to participate ins study; rep sample

sample

take results from sample and make claims about population

generalize

how many people are in sample

sample size

what's the diff between large and small sample size

large: detect small diffs small: less money and time

having complete list of population and likely of being selected into study

probability sampling

everybody in list has an equal chance of being asked to be in study

sample random sampling

you have these people's info in advance, you make the proportion in sample equal pop

stratified random sampling

when you don't know the names of everybody that match pop | can't tell odds of being in study

nonprobability sampling

whoever happens to be available atm | have access to

convenience sampling

target group you are trying to access

purposive sampling

once you have identified what type of people you care asking, you ask their friends once you find a person w a char you want, you ask for additional named for that category

snowball sampling

nonprobability ver of stratified random sampling

quota sampling

the researcher did something wrong in study

systematic sampling error

some groups could be overrepresented | if you follow a sampling plan, this is ok

random sampling error

correlations are looking for co-relationships asking people to submit data to us association claims/relational research

correlational design

at least 2 variables collected from each person

bivariate

importance of correlations

widely used | predictive devices

probs w correlation

directionality prob | 3rd variable prob

unsure which variable was the cause

directionality prob

there might be something else out there that might be affecting both variables

3rd variable prib

number of scores you get from people, you can't discriminate them

restricted range

everybody scored similarly, but scored poorly

floor effect

everybody scored similarly, but scored highly

ceiling effect

if someone scores very diff than other scores then it impacts the statistical coefficient scatter plot can show this visually

outlier prob

a decimal score ranges from -1 to 1 how strong the relationship is the closer you get to 0, the more likely theres no association

magnitude

used for only 1 IV has only 2 groups the bigger the value, the more diff the groups are value can be pos or neg

t-test

only uses 1 IV can use 2+ groups bigger the value, the bigger the diff has to be a pos value

ANOVA

2 diff groups' effect of IV | very systematic

between group variance

effect of extraneous variables random pooled variance

within group variance

exam 2 Flashcards

(134 cards)