Stats Vocab for Part 1 (copy)

facts that convey information; set values or characters with some information about those (ex. yearly average global surface air temperatures)

contains all of the items or individuals of interest that you seek to study

a subset of the target population from which conclusions about the target population will be drawn (ex. 20 WPI students)

to obtain observations from every sampling unit in the population

an entity on which measurements or observations can be made (ex. a single student in WPI)

a collection of sampling units about which we want to draw conclusions (ex. all WPI students)

a list of all sampling units in the target population (ex. a list of all WPI student ID’s'; phone numbers)

how you get your sample; a pattern, arrangement or method used for selecting a sample of sampling units from the target population (ex. simple random sample)

the operational plan, including the sampling design, for actually obtaining or accessing the sampling units for the study (ex. interview, survey, phone interview)

a physical entity that is the primary unit of interest in a specific research objective (ex. the test sheets at the ink company)

a measurement or observation of interest that is made on an experimental unit (ex. improper inked area in mm^2)

a quantity that is thought to influence the response (experimental & nuisance)

a factor that is purposely varied by the experimenter (ex. ink flow setting; pressure plate setting)

a factor that cannot be controlled by the experimenter. May or may not be known to the experimenter (ex. temperature of the room; quality of the paper)

a value assumed by a factor in an experiment (ex. ink flow- high/low; pressure plates- high/medium/low)

the combinations of levels of experimental factors for which the response will be observed (ex. low+low, low+med, low+high, etc.)

the change in the average response between two factor levels or between two combinations of factor levels (ex. the effect of high pressure plate setting(23.025) over medium pressure plate setting(25) is 23.025-25= -1.975)

study in which treatments are imposed on experimental units in order to observe a response (ex. keeping ink flow the same; maintaining temperature)

items included are chosen without regard to their probability of occurence

items are selected based only on the fact that they are easy, inexpensive, or convenient to sample

get opinions of preselected experts in the subject matter (ex. study of an illness- a doctor)

method of choosing a sample using a pre-specified chance of mechanism

each possible sample has the same chance of selection; good if units are homogeneous and easily assessed (ex. table of random numbers; computer random number generators)

selected individuals are returned to frame for possible reselection

selected individual is NOT returned to the frame

units are divided into distinct strata (homogeneous subgroups), and a simple random sample taken separately in each subgroup (ex. break school up by major, then SRS)

population is divided into “k” groups called clusters, researchers randomly select n clusters to include in sample (ex. randomly choose 5 flights that depart that day and survey all passengers)

all elements within the selected clusters are included in the sample

sample is taken in stages (ex. a sample of 300 counties in US is chosen, then a sample of townships within each of selected counties is chosen, then a sample of city blocks within selected townships, then sample of households is chosen)

designed to observe each “k”th individual in a process (ex. suppose you take a systematic sample of n=40 for the population of N=800 employees. Subgroups will each contain k=20 employees. Select a random number 1-20. Suppose you chose 8. Selections are 8, 28, 48, 68…788)

error obtained when, due to chance, a sample quantity give results different than the analogous population quantity. Not a result of a mistake, and will occur even when everything in the sampling plan has been done correctly

result of being unable to sample from entire population, misleading or false measurements (ex. selection bias, nonresponse bias, response bias)

bias that results from an unrepresentative sample (ex. radio station asking listeners if they like that radio station)

occurs in studies of human populations when questions are phrased in a manner which is difficult to understand or in a fashion that makes a particular answer seem more desirable to the respondent (ex. asking if someone is using drugs)

failure to collect data on all items in the sample; cannot assume that a person who did not respond is similar to those who did

the name given to what is being measured, counted, or observed when data are collected (ex. height, weight, GPA)

summarizes the value of a population for specific variable (ex. average height of a man in the USA)

summarizes the value of a specific variable for sample data (ex. average height of a man in MA)

qualitative; variables take categories as their values (ex. eye color)

quantitative; variables have values that represent a counted or measurement quantity (ex. height 120, 130, 170)

There is order and ranking in the variable (ex. freshman, sophmore, junior, senior military ranking)

No order or ranking is implied (ex. eye color)

Values can drop below zero (ex. temperature)

Values cannot drop below zero (ex. number of pets, weight)

methods that primarily help summarizing and presenting data

Methods that use data collected from a sample to reach conclusions about a population

variables such as number of family members, or pets

variables such as height or weight