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Chapter One Assignment Definitions Section1-1

1. Data- Are collections of observations (such as measurements, genders, surveyresponses).

2. Statistics- is the science of planning studies and experiments, obtaining data, and thenorganizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions

based on the data.

3. Population- is the complete collection of all individuals (scores, people, measurements,and so on) to be studied. The collection is complete in the sense that it includes allof

the individuals to be studied.

4. Census- is the collection of data from everymember of the population.5. Sample- is a subcollection of members selected from a population.

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6. Parameter- is a numerical measurement describing some characteristic of apopulation.7. Statistic- is a numerical measurement describing some characteristic of a sample.8. Quantitative (or numerical) data- consist ofnumbers representing counts or

measurements.

9. Categorical (or qualitative or attribute) data- consist of names or labels that are notnumbers representing counts or measurements.

10.Discrete data- results when the number of possible values is either a finite number or acountable number. (That is, the number of possible values is 0 or 1 or 2, and so on).

11.Continuous (numerical) data- results from infinitely many possible values thatcorrespond to some continuous scale that covers a range of values without gaps,

interruption, or jumps.

12.Nominal level of measurement- is characterized by data that consist of names, labels,or categories only. The data cannot be arranged in an ordering scheme (such as low to

high).

13.Ordinal level of measurement- Data are at the ordinal level of measurement if they canbe arranged in some order, but differences (obtained by subtraction) between data

values either cannot be determined or are meaningless.

14.Interval level of measurement- is like the ordinal level, with the additional property thatthe difference between any two data values is meaningful. However, data at this level

do not have a naturalzero starting point (where none of the quantity is present).

15.Ratio level of measurement- is the interval level with the additional property that thereis also a natural zero starting point (where zero indicates that none of the quantity is

present). For values at this level, differences and ratios are both meaningful.

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16.Observational study- we observe and measure specific characteristics, but we dontattempt to modifythe subjects being studied.

17.Experiment- we apply some treatmentand then proceed to observe its effects on thesubjects. (Subjects in experiments are called experimental units.)

18.Simple random sample- ofn subjects is selected in such a way that every possiblesample of the same size n has the same chance of being chosen.

19.Random sample- members from the population are selected in such a way that eachindividual memberin the population has an equal chance of being selected.

20.Probability sample- involves selecting members from a population in such a way thateach member of the population has a known (but not necessarily the same) chance of

being selected.

21.Systematic sampling- we select some starting point and then select every kth (such asevery 50

th) element in the population.

22.Convenience sampling- we simply use results that are very easy to get.23.Stratified sampling- subdivide the population into at least two different subgroups (or

strata) so that subjects within the same subgroup share the same characteristics (such

as gender or age bracket), then we draw a sample from each subgroup (or stratum).

24.Cluster sampling- first divide the population area into sections (or clusters), thenrandomly select some of those clusters, and then choose allthe members from those

selected clusters.

25.Cross-sectional study- data are observed, measured, and collected at one point in time.26.Retrospective (or case-control)study- data collected from the past by going back in time

(through examination of records, interviews, and so on).

27.Prospective (or longitudinal or cohort) study- data are collected in the future fromgroups sharing common factors (called cohorts).

28.Confounding- occurs in an experiment when you are not able to distinguish among theeffects of different factors.

29.Sampling error- is the difference between a sample result and the true populationresult; such an error results from chance sample fluctuations.

30.Nonsampling error- occurs when the sample data are incorrectly collected, recorded, oranalyzed (such as by selecting a biased sample, using a defective measurement

instrument, or copying the data incorrectly).