Study your flashcards anywhere!
Download the official Cram app for free >
 Shuffle
Toggle OnToggle Off
 Alphabetize
Toggle OnToggle Off
 Front First
Toggle OnToggle Off
 Both Sides
Toggle OnToggle Off
 Read
Toggle OnToggle Off
How to study your flashcards.
Right/Left arrow keys: Navigate between flashcards.right arrow keyleft arrow key
Up/Down arrow keys: Flip the card between the front and back.down keyup key
H key: Show hint (3rd side).h key
A key: Read text to speech.a key
58 Cards in this Set
 Front
 Back
statistics

the art of collecting and organizing data as well as drawing inferences from the data


descriptive statistics

collecting
organizing summarizing describing 

inferential statistics

drawing conclusions from the data


variable

a characteristic that takes on different values for different people and places and things (must vary)


quantitative variable

a variable that can be measured in the usual sense


qualitative variable

a characteristic that cannot be measured in the usual sense  categorical


population

the largest collection of entities for which we have an interest at a particular time


sample

a subset of the population


well representative sample

when the characteristics of the sample match the characteristics of the population


parameter

numerical value based on the population


statistic

a numerical value based on the sample


measurement

the assignment of numbers to objects or events according to a set of rules


four types of measurement

nominal scale
ordinal scale interval scale ratio scale 

nominal scale

"naming observations" or classifying them into various mutually exclusive categories (ex: male/female)


ordinal scale

measurements can be ranked according to some criterion: low/average/high


interval scale

measurements can not only be ranked but the distance btwn the two is known  no true zero pt


ratio scale

measurements in which equality of ratios as well as equality of intervals is known  no true zero pt


methods for obtaining data

census
sampling experimentation 

census

get info from every element of the pop


two types of samples

nonprobability and probability


examples of nonprobability samples

sample of convenience
haphazard selection judgment sampling expert sampling quota sampling 

sample of convenience

samples already exist


haphazard selection

subjects casually met


judgment sampling

the researcher uses his/her own judgment in choosing the subjects


expert sampling

an "expert" picks the subjects


quota sampling

subjects are chosen so as to satisfy certain quotas (can also be probability sampling)


probability samples

when the sample is obtained by a chance process


types of probability samples

random samples
stratified samples cluster samples systematic sampling 

random samples

all samples of the same size have equal probability of being selected


stratified samples

population is divided into subpops (strata) and a random sample is obtained from each strata


cluster samples

randomly selecting some of the strata and obtaining a random sample from the chosen strata (subjects are naturally clustered together)


systematic sampling

choose a random starting pt from a list of subjs and then select every nth subject on the list


selection bias

when exclude a specific characteristic or segment of the population


response bias

when subjects respond incorrectly by lying or exaggerating or forgetting or not understanding the question (misleading question)


nonresponse bias

when the response rate is low


two "types" of experiments

observational study
designed experiment 

observational study

simply comparing two or more groups  only shows association


designed experiment

 control
 randomization (div subjs into groups)  replication 

treatment group

the group that receives the treatment


control group

group that does not receive the treatment


blind study

when the subjects don't know if they are receiving the treatment or placebo


doubleblind study

neither the subjects nor the doctors know if subjects are in the treatment or control group


problems w/ experiments

placebo effect
hawthorne effect rosenthall effect 

placebo effect

when subjects improve because they believe they are receiving the treatment


rosenthall effect

when the researcher or experimenter unintentionally influences the outcome thru facial expressions or body lang or voice


hawthorne effect

when the outcome is affected because people change how they behave because they know they are being watched


frequency distribution

dot plot


grouped freq distribution

by age or grade
histogram 

relative freq distribution

percent


measure of central tendency

conveys a "typical" value of the data set
ex: mean; median; mode 

properties of mean

most commonly used
may not be a value in the data set is not a resistance measure: mean will change when a value changes 

median

value such that 50% of the data is smaller and 50% of the data is larger


find location of median

(n+1)/2


properties of median

may not be a value in the data set
is a resistance measure: median won't change when a value changes 

resistance measure

a measure that is not affected by outliers


measures of dispersion

conveys info abt the amt of variability in the data:
range variance standard deviation interquartile range 

variance

measures the variability by comparing each data value to the mean
 not a resistance measure 

standard deviation

measures the variability in original units
 not a resistance measure 