Chapter 1: Introduction to Statistics Flashcards

1
Q

Define data.

A

Collections of observations, such as measurements, genders, or survey responses.

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2
Q

Define statistics.

A

The science of planning studies and experiments; obtaining data; and then organizing, summarizing, presenting, analyzing, and interpreting those data and then drawing conclusions based on them.

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3
Q

Define population.

A

The complete collection of ALL measurements or data that are being considered.

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4
Q

Define census.

A

The collection of data from EVERY member of the population.

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5
Q

Define sample.

A

A SUBCOLLECTION of members selected from a population.

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6
Q

What is a voluntary response sample?

A

One in which the volunteers themselves decide whether to be included.

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7
Q

When are results considered to be statistically significant?

A

When it is very unlikely that they occurred by chance.

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8
Q

What makes a treatment or finding have practical significance?

A

When common sense suggests that it makes enough sense to justify its use and be practical.

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9
Q

Does correlation imply causation?

A

No way!

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10
Q

Define parameter.

A

A numerical measurement describing some characteristic of a population.

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11
Q

Define statistic.

A

A numerical measurement describing some characteristic of a sample.

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12
Q

Define quantitative data.

A

Data that consists of numbers representing counts or measurements.

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13
Q

Define categorical (or qualitative/attribute) data.

A

Data that consists of names or labels that are not numbers representing counts or measurements.

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14
Q

When is data considered to be discrete?

A

When the values are quantitative and the number of values is finite or “countable.”

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15
Q

When is numerical data considered to be continuous?

A

When there are infinitely many possible values, where the collection of values is not countable. (That is, it is impossible to count the individual items because at least some of them are on a continuous scale, such as lengths from 0 cm to 12 cm.)

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16
Q

nominal level of measurement

A

data that consist of names, labels, or categories only. The data cannot be arranged in an ordering scheme (such as low to high).

17
Q

What are some examples of sample data at the nominal level of measurement?

A

Survey responses of yes, no, and undecided; political party affiliation; and social security numbers.

18
Q

ordinal level of measurement

A

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

19
Q

What are some examples of data at the ordinal level of measurement?

A

Course grades, ranks, feedback scales.

20
Q

What does ordinal data provide information about?

A

Relative comparisons, but not the magnitude of the differences.

21
Q

interval level of measurement

A

Differences are meaningful, but there is no natural zero starting point and ratios are meaningless.

22
Q

Do data at the interval level of measurement have a natural zero starting point at which none of the quantity is present?

A

Nope.

23
Q

What are some examples of data at the interval level of measurement?

A

Outdoor and body temperatures, years

24
Q

ratio level of measurement

A

Data that can be arranged in order, differences can be found and are meaningful, and there is a natural zero starting point (where zero indicates that none of the quantity is present). For data at this level, differences and ratios are both meaningful.

25
Q

What are some examples of data at the ratio level of measurement?

A

Heights, lengths, distances, volumes