Chapter 1- Vocab. Flashcards

1
Q

Data.

A

Observations such as measurements, genders, and survey responses that have been collected.

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2
Q

Statistics.

A

A collection of methods for planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data.

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3
Q

Population.

A

The complete collection of all elements such as scores, people, measurements, etc. to be studied. The collection is complete in the sense that it includes all subjects to be studied.

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4
Q

Census.

A

The collection of data from every member of the population.

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5
Q

Sample.

A

A subcollection of members selected from a population.

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6
Q

Parameter.

A

A numerical measurement describing some characteristic of a population.

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7
Q

Statistic.

A

A numerical measurement describing some characteristic of a sample.

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8
Q

Qualitative Data.

A

Data separated into different categories that are distinguished by some non-numeric characteristic.

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9
Q

Quantitative Data.

A

Data that consists of numbers representing counts or measurements.

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10
Q

Discrete Data.

A

Data results when the number of possible values is either a finite number or a countable number.

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11
Q

Continuous Data.

A

Data results from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions or jumps.

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12
Q

Nominal.

A

Characterized by data that consists of names, labels, or categories only.

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13
Q

Ordinal.

A

Data that can be arranged in some order, but differences between data values either cannot be determined or are meaningless.

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14
Q

Interval.

A

The difference between any two data values is Meaningful. However, data at this level do not have a natural zero starting point.

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15
Q

Ratio.

A

Data that has a natural zero starting point.

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16
Q

Voluntary Response Sample.

A

A sample in which the respondents themselves decide whether to be included.

17
Q

Loaded Question.

A

Questions that are intentionally waited to elicit a desired response.

18
Q

Observational Study.

A

Observe and measure specific characteristics, but we don’t attempt to modify the subjects being studied.

19
Q

Experiment.

A

Apply some treatment and then proceed to observe its effects on the subjects.

20
Q

Cross-Sectional Study.

A

Data are observed, measured, and collected at one point in time.

21
Q

Retrospective Study.

A

Data are collected from the past by going back in time (through the examination of records, interviews, and so on).

22
Q

Prospective or Longitudinal Study.

A

Data are collected in the future from groups sharing common factors.

23
Q

Confounding.

A

When you are not able to distinguish among the effects of different factors in an experiment.

24
Q

Blinding.

A

A technique in which the subject doesn’t know whether he or she is receiving a treatment or a placebo.

25
Q

Placebo Effect.

A

Untreated subject reports an improvement in symptoms in an experiment

26
Q

Double Blind Experiment.

A

Blinding occurs at two levels: the person administering the experiment and the participants are not aware of who receives treatment or a placebo.

27
Q

Block.

A

A group of subjects that are similar.

28
Q

Replication.

A

The repetition or duplication of an experiment so that results can be confirmed or verified.

29
Q

Random Sample.

A

Members from the population are selected in such a way that each individual member has an equal chance of being selected.

30
Q

Convenience Sampling.

A

Simply use results that are very easy to get.

31
Q

Stratified Sampling.

A

Subdivide the population into at least two different subgroups so that subjects within the same subgroup share the same characteristics, then we draw a sample from each subgroup.

32
Q

Cluster Sampling.

A

First divide the population area into sections, then randomly select some of those sections, and then choose all the members from the selected sections.

33
Q

Systematic Sampling.

A

Select some starting point and then select every element in the population.

34
Q

Sampling Error.

A

The difference between a sample result and the true population results.

35
Q

Non-Sampling Error.

A

Occurs when the sample data are incorrectly collected, recorded, or analyzed.