Stats Terms

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statistics

Back 1

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

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descriptive statistics

Back 2

collecting
organizing
summarizing
describing

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inferential statistics

Back 3

drawing conclusions from the data

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variable

Back 4

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

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quantitative variable

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a variable that can be measured in the usual sense

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qualitative variable

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a characteristic that cannot be measured in the usual sense - categorical

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population

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

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sample

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a subset of the population

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well representative sample

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

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parameter

Back 10

numerical value based on the population

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statistic

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a numerical value based on the sample

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measurement

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

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four types of measurement

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nominal scale
ordinal scale
interval scale
ratio scale

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nominal scale

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

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ordinal scale

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

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interval scale

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

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ratio scale

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

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methods for obtaining data

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census
sampling
experimentation

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census

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get info from every element of the pop

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two types of samples

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nonprobability and probability

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examples of nonprobability samples

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sample of convenience
haphazard selection
judgment sampling
expert sampling
quota sampling

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sample of convenience

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samples already exist

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haphazard selection

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subjects casually met

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judgment sampling

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

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expert sampling

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an "expert" picks the subjects

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quota sampling

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

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probability samples

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when the sample is obtained by a chance process

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types of probability samples

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random samples
stratified samples
cluster samples
systematic sampling

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random samples

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

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stratified samples

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

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cluster samples

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

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systematic sampling

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

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selection bias

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when exclude a specific characteristic or segment of the population

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response bias

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

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nonresponse bias

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when the response rate is low

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two "types" of experiments

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observational study
designed experiment

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observational study

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simply comparing two or more groups - only shows association

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designed experiment

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- control
- randomization (div subjs into groups)
- replication

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treatment group

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the group that receives the treatment

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control group

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group that does not receive the treatment

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blind study

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

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double-blind study

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

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problems w/ experiments

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placebo effect
hawthorne effect
rosenthall effect

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placebo effect

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when subjects improve because they believe they are receiving the treatment

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rosenthall effect

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

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hawthorne effect

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

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frequency distribution

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dot plot

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grouped freq distribution

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by age or grade
histogram

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relative freq distribution

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percent

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measure of central tendency

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conveys a "typical" value of the data set

ex: mean; median; mode

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properties of mean

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

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median

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

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find location of median

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(n+1)/2

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properties of median

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

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resistance measure

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a measure that is not affected by outliers

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measures of dispersion

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conveys info abt the amt of variability in the data:

range
variance
standard deviation
interquartile range

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variance

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measures the variability by comparing each data value to the mean

-- not a resistance measure

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standard deviation

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measures the variability in original units

-- not a resistance measure