intro to experimental exam 2

self-report measure

Operationalize a variable by recording people’s answers to questions about themselves in a questionnaire or interview

observational measure

Operationalize a variable by recording observable behaviors

physiological measure

operationalize a variable by recording biological data (e.g., brain activity, hormonal levels, heart rate)

categorical (nominal) variable

levels of the variable are qualitatively distinct. the order of the levels doesn’t matter

quantitative variable

ordinal scale

categories in an ordered sequence. place data in a ranked order, but doesn’t tell us anything about numerical differences between categories

interval scale

ordered categories with equal intervals between categories, places data in order with equivalent distances between the ordered categories. doesn’t have a meaningful zero

reliability

consistency of a measurement device

validity

how much measurements actually represent what you think you’re measuring

test-retest validity

the consistency in responses across time points

interrater reliability

do two individuals use the operational definition the same way?

internal reliability

many tests attempt to measure a variable with multiple items

correlation coefficient (r)

Measures the strength and the direction of the relationship between two variables

• ranges from -1 to +1, with 0 indicating no association

• If r is large (i.e. close to 1), there is a strong relationship between the 2 variables

  • This will form a straight line

• Is r is small (i.e. close to 0), there is a weak relationship between the 2 variables

  • This will form a horizontal/flat line 

strength

cronbach’s alpha

average correlation of all items; to what extent do they measure the same thing; how much are items that should be related correlated

face validity

does the measure appear to measure what it’s supposed to measure

content validity

the extent to which a measuring instrument covers all dimensions of a construct

criterion validity

does the measure allow you to distinguish people on the basis of particular behavioral outcomes?

convergent validity

measure is correlated with other measures of the same concept/variable

discriminant validity

measure is not correlated with measures of a different concept/variable

what is measurement?

what are the types of measurement?

Self-report measures

observational

physiological

what are the scales of measurement?

ratio scales, interval scales, likert scale

how do we measure constructs consistently?

how do we evaluate the validity of measures?

survey poll

a method of posing questions to people on the telephone, in person interviews, on written questionnaires, or via the internet 

open ended question

allows respondents to answer any way they like
example: what is your favorite color?

forced choice question

people give their opinion by picking the best of two or more options

example: select your favorite color from this list

likert scale

a survey question format using a rating scale containing multiple response options anchored by the specific terms (strongly agree, agree, neither agree nor disagree, disagree, strongly disagree)

leading question

wording encourages one response more than others

double barreled question

asking two questions in one

negatively worded question

• negatively phrased questions 

  • Example: people who do not drive with a suspended license should never be punished 

  • Negative wording takes more time to process, and makes it more difficult

response set

• answering a number of questions in the same way

  • Can use attention checks in surveys to see if people are paying attention 

acquiescence

“strongly agree” to all possible options

fence sitting

• answer the middle option for all responses

  • Can remove the center of the scale to people have to pick a side

socially desirable responding/faking good

trying to look better than we are

faking bad

try to look bad (more aggressive, more deviant, nastier)

observational research

observer bias

when observers see what they expect to see

observer effect

when participants confirm observer expectations (expectancy effects)

masked design

the observers do not know to which conditions the participants have been assigned, and they are not aware of what the study is about

reactivity

• when participants react to being watched 

  • Solution 1: blend in 

    • Unobtrusive observations 

  • Solution 2: Wait it out 

  • Solution 3: Measure the Behavior’s Results

what are the different types of question formats?

• open-ended questions

• forced-choice questions

• likert scale

• Semantic Differential format

what should you not do when writing a question?

DO NOT USE

• leading questions

• double-barreled questions

• negative wording

what are the things you need to be mindful of when designing your survey (wording effects and order effects)?

how can we encourage accurate responding?

population

the entire set of people or things in which you are interested

sample

the smaller set of people or things that is taken from the population

biased sample

unrepresentative sample- not all members of a population have an equal probability of being included

unbiased sample

 representative sample- all members of the population have an equal probability of being included

convenience sample

using a sample of people who are easy to contact and readily available to participate 

• Sampling only those who volunteer 

self-selection

a type of biased sampling in which only people who volunteer participate in a study. Self-selection is especially prevalent in online polls

snowball sampling

A variation on purposive sampling in which participants are asked to recommend other participants for the study

probability sampling

every member of the population of interest has an equal chance of being selected for the sample

simple random sample

obtained by putting every member’s name of your population of interest in a pool and then randomly selecting a predetermined number of names from the pool to include in your sample 

stratified random sampling

a multistage technique in which the researcher selects specific demographic categories (such as race or gender) and then randomly selects individuals from each of the categories 

systematic sampling

random assignment

a research technique that uses chance to assign participants to groups in an experiment

purposive sampling

quota sampling

Similar to stratified random sampling; the researcher identifies subsets of the population and then sets a target number (i.e., a quota) for each category in the sample. Then uses nonrandom sampling until the quotas are filled

when is it important to use a representative sample and why?

bivariate correlation

associations that involve exactly two variables

chi-square

t-test

effect size

statistical significance

outlier

• An outlier is an extremely deviant individual in the sample

• Characterized by a much larger (or smaller) score than all the others in the sample

• In a scatter plot, the point is clearly different from all the other points

• Outliers produce a disproportionately large impact on the correlation coefficient

restriction of range

directionality problem

third variable problem

spurious association

moderator or modifier

what are correlations?

are variables measured or manipulated in a correlational study?

what is a statistic you would use when you have two categorical variables?

what is a statistic you would use when you have two quantitative variables?

what is a statistic you would use when you have a categorical and quantitative variable?

what is effect size?

what is statistical significance?

what does a non-significant effect mean?

can we make a causal claim with a bivariate correlation?

descriptive statistics

inferential statistics

central tendency

 to find a single value that best represents the entire distribution of scores

measures allow us to summarize or describe a large group of scores

mean

• Sum of scores divided by the number of scores 

• Amount each individual receives when the total is divided equally among all individuals in the distribution 

• The balance point for distribution

median

• Midpoint of the scores in a distribution when they are listed in order from smallest to largest

• Divides the scores into two groups of equal size

mode

• Score with the greatest frequency of any score in the distribution 

  • Can be used with any scale of measurement

  • Corresponds to an actual score in the data set

• It is possible to have more than one mode

  • Called bimodal or multimodal distributions 

• To calculate the mode, simply find the most common response

bimodal

multimodal

variance

• measures the average squared distance from the mean 

  • Used mostly for calculations 

standard deviation

measures the standard (average) distance of the scores from the mean

degrees of freedom

what are the measures of central tendency and when should each of them be used?

what is positive skew?

what is negative skew?

how does the distribution effect each measure of central tendency?

what is variance?

what is standard deviation?

what are the degrees of freedom, and why are they important?