Ch 1: Intro to Statistics

Data

collections of observations (such as measurements, genders, survey responses)

Statistics

is the science of planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data

Population

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 all of the individuals to be studied

Census

Collection of data from every

member of a population

Sample

Subcollection of members

selected from a population

Sample data must be

random

Context

What do the values represent? Where did the data come from? Why were they collected?

An understanding of the context will directly affect the statistical procedure used.

Source of data

Is the source objective? Is the source biased? Is there some incentive to distort or spin results to support some self- serving position? Is there something to gain or lose by distorting results?

Be vigilant and skeptical of studies from sources that may be biased.

Sampling Method

Does the method chosen greatly influence the validity of the conclusion? Voluntary response (or self-selected) samples often have bias (those with special interest are more likely to participate). These samples' results are not necessarily valid. Other methods are more likely to produce good results.

Statistical Significance

If the likelihood of getting the results is so small, then the results are

Parameter

a numerical measurement

describing some characteristic of a population.

Statistic

a numerical measurement describing

some characteristic of a sample.

Quantitative (or numerical) data

consists of numbers representing counts

or measurements.

Categorical (or qualitative or attribute) data

consists of names or labels (representing categories)

Discrete quantitative data

result when the number of possible values is either a finite number or a 'countable' number

(i.e. the number of possible values is 0, 1, 2, 3, . . .)

Continuous (numerical) quantitative data

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

Nominal level of measurement

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

Ordinal level of measurement

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

Interval level of measurement

like the ordinal level, with the additional property that the difference between any two data values is meaningful, however, there is no natural zero starting point (where none of the quantity is present)

Ratio level of measurement

the interval level with the additional property that there is 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 meaningful