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Summary Discovering Statistics Using SPSS by Andy Field Chapters 1-6 Summaries
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Notes and summaries of Chapters 1-6 on Andy Field's Discovering Statistics Using SPSS. Intermediate Statistics I.
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Intermediate Statistics I Book Chapter NotesChapter 1
The research process
Variables
Levels of Measurement
Measurement error there is often a discrepancy between the numbers used
to represent the thing that is being measured and the actual value of the thing
that is being measured, this discrepancy is called the measurement error
Validity and reliability
- Validity: whether an instrument actually measures what it sets out to
measure
, - Reliability: whether an instrument can be interpreted consistently across
different situations
- Criterion validity: whether you can establish that an instrument
measures what it claims to measure through comparison to objective
criteria
o When data are recorded simultaneously using the new instrument
and existing criteria, it is said to assess concurrent validity
o When data from the new instrument are used to predict
observations at a later point in time it is said to assess predictive
validity
Correlational research methods
- Correlational or cross-sectional research: observes what naturally goes
on in the world without directly interfering with it
- Experimental research: one variable is manipulated
Systematic variation: this variation is due to the experimenter doing something
in one condition but not in the other condition
Unsystematic variation: this variation results from random factors that exist
between the experimental conditions (such as natural differences in ability, the
time of day etc)
Randomization
- Keeping the unsystematic variation as small as possible so that you get a
more sensitive measure of the experimental manipulation
- Practice effects: participants may perform differently in the second
condition of familiarity with the experimental situation and/or the
measure being used
- Boredom effects: participants may perform differently in the second
condition because they are tired or bored of the first condition
1.6 Analyzing Data
Frequency distribution/histogram: a graph plotting values of observations on
the horizontal axis – can be useful for assessing properties of the distribution of
scores
Normal distribution: where data is distributed symmetrically around the
center of all scores
, The center of a distribution – central tendency (measuring where the center of a
frequency distribution lies): mode, median and the mean
The dispersion in a distribution
- Range: take the largest score and subtract from the smallest score
- Interquartile range: the middle 50% of the scores
- Quartiles: the three values that split the sorted data into equal parts
o First calculate the median (or second quartile), splits data into two
parts
o Lower quartile
o Upper quartile
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