Chapter 3 Flashcards by Peter Eliazar Dizon

Act of assigning numbers or symbols to characteristics of things according to rules

Measurement

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Collective influence of all of the factors on a test score beyond those specifically measured by the test

Error

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Set of numbers whose properties model empirical properties of the objects to which the numbers are assigned

Scales

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Measures continuous variables

Continuous Scale

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Categorization has no much meaning

Discrete Scale

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The property of “moreness”

Magnitude

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The difference between two points at any place on the scale has the same meaning as the difference between two other points that differ by the same number of scale units

Equal Intervals

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Obtained when nothing of the property being measured exists

Absolute Zero

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Classification or categorization based on one or more distinguishing characteristics

Nominal Scale

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Classification and ranking or ordering

Ordinal Scale

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Classification and ranking and equal intervals; no absolute zero

Interval Scale

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All math operations can be meaningfully performed; has absolute zero

Ratio Scale

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Most frequently used scale in psychology

Ordinal

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A set of test scores arrayed for recording or study

Distribution

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Straightforward, unmodified accounting of performance that is usually numerical

Raw Score

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Where all scores are listed alongside the number of times each score occurred presented in graphic or tabular form

Frequency Distributions

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Test-score intervals/class intervals replace the actual test scores

Grouped Frequency Distribution

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Highest score minus lowest score

Range

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Diagram or chart composed of lines, points, bars, or other symbols that describe and illustrate data

Graph

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A graph with vertical lines drawn at the true limits of each test score forming a series of contiguous rectangles.

Histogram

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Abscissa; score

X-axis

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Ordinate; frequency of occurrence

Y-Axis

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Parang life support

Frequency Polygon

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It answers the question “what percent of the scores fall below a particular score (Xi)?; the percentage of scores in its frequency distribution that are equal to or lower than it. Pr = B/N x 100

Percentile Ranks

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The specific scores or points within a distribution; divide the total frequency for a set of observations into hundredths

Percentiles

A statistic that indicates the average or midmost score between the extreme scores in a distribution

Measures of Central Tendency

Also called as average; takes into account the actual numerical value of every score

Mean

X = Σ(X/n)

sum of observation divided by number of observation

X = Σ(fX)n

Computing mean from Frequency Distribution; "multiply the frequency of each score by its corresponding score and then sum"

Bell Shape

Normal Curve or Gaussian curve, probability curve (Carl Friedrich Gauss)

Below and above average

Bimodal Distribution

The score is located at -1; low scorer; low/below average

Positively Skewed Distribution

The score is located at +1; high scorer; high/above average

Negatively Skewed Distribution

Depicts a trend that starts with a sharp drop and is followed by a dramatic rise. The trendline ends in an improvement from the starting point

J-shaped curve

Scores are equal

Rectangular Distribution

Middle score; get by ordering. If the number of scores is even, sum up the two middle scores and divide it by 2

Median

Getting the most frequently occurring score

Mode

Indication of how scores in a distribution are scattered or dispersed

Range (HS - LS)

Dividing points between the four quarters in the distribution; specific points - Interval

Quartiles - Quarter

Measure of variability equal to the difference between Q3 and Q1 (Q1 - Q2)

Interquartile Range

Q1 - Q2/2

Semi-Interquartile Range

Another tool to describe amount of variability in distribution (AD = Σ|x|/n) X = mean - score Bars = absolute value

Average Deviation

Measure of variability equal to the square root of the average squared deviations about the mean

Standard Deviation

s2 = Σx2/n

Variance: The arithmetic mean of the squares of the differences between the scores in a distribution and their mean (sigma)

Indication of how the measurements in a distribution are distributed

Skewness

When relatively few of the scores fall at the high end of the distribution; may indicate that the test was too difficult

Positive Skew

When relatively few of the scores fall at the low end of the distribution; may indicate that the test was too easy

Negatively Skew

The steepness of a distribution in its center; root - kurtic

Kurtosis

Relatively flat (average level)

Platykurtic

Relatively peaked

Leptokurtic

Somewhere in the middle (normal curve)

Mesokurtic

Bell-shaped, smooth, mathematically defined curve that is highest at its center

Normal Curve or Laplace-Gaussian Curve

The one credited with being the first to refer to the curve as the NORMAL curve

Karl Pearson

Area on the normal curve between 2 and 3 standard deviations above the mean

Tails

It is the score minus mean divided by variance

Z-score

Pioneered the T-score

William Anderson McCall

The T-test [T = (z x 10) + 50 was named after

Edward Lee Thorndike

Standard and nine

Stanine [Stanine = (z x 2) + 5]

Retains a direct numerical relationship to the original raw score.

Linear Transformation

Required when the data under consideration are not normally distributed yet comparisons with normal distributions need to be made; no direct relationship

Nonlinear Transformation

Normal curve with corresponding scale of standard scores

Normalized Standard Scores

Normalize an abnormal curve

Stretching

Provides us with an index of the strength of the relationship between two things (r)

Correlation Coefficient

Expression of the degree and direction of correspondence between two things

Correlation

Devised by Karl Pearson (Para); used only if the relationship is linear; can be furthered by Coefficient of Determination (r2). Indication of how much variance is shared by the X- and the Y-variables; square the correlation coefficient and multiply by 100. It is used when variables are Linear and Continuous.

Pearson r, Pearson correlation coefficient, Pearson product-moment coefficient of correlation.

Pearson and Z-score are correlated because both are concerned with the location of an individual in a distribution

An indication of how much variance is shared by the X and Y variables; evaluates the strength and relationship

Coefficient of Determinism

Describes a deviation about a mean of a distribution

Moment

Individual deviations about the mean of a distribution; first moments of the distribution

Deviates

Moments squared - moments cubed

Second Moments - Third Moments

Rank-order/rank-difference correlation-coefficient; alternative (non-para sample size is small; fewer than 30 pairs); developed by Charles Spearman

Spearman Rho

An expression of the degree and direction of correspondence between two things (Degree: Weak - strong; Direction: Positive, negative, no correlation; LINEAR relationship; only TWO variables; Numerical in nature; no causation but can predict

Correlation

Bivariate distribution/scatter diagram/scattergram; simple graphing of the coordinate points for values of the x-variable and the y-variable; provide quick information of direction and magnitude

Scatterplot

Refers to the "eyeball gauge" of how curved a graph is

Curvilinearity

An extreme atypical point located at a relatively long distance from the rest of the coordinate points in a scatterplot

Outlier

Analysis of the data from several studies

Meta-Analysis

Chapter 3 Flashcards

(76 cards)