Chapter 1 Flashcards
Another name for Independent Design
Between-groups design
A description of a distribution of observations that has two modes
Bimodal
A categorical variable that has only two mutually exclusive categories (e.g., being dead or alive).
Binary variable
Refers to the possibility that performance in tasks may be influenced (the assumption is a negative influence) by boredom or lack of concentration if there are many tasks, or the task goes on for a long period of time.
Boredom effect
What is a categorical variable?
a variable that can take on one of a limited, and usually fixed, number of possible values, assigning each individual or other unit of observation to a particular group or nominal category on the basis of some qualitative property
A generic term describing the centre of a frequency distribution of observations as measured by the mean, mode and median.
Central tendency
a form of criterion validity where there is evidence that scores from an instrument correspond to concurrently recorded external measures conceptually related to the measured construct.
Concurrent validity
a variable (that we may or may not have measured) other than the predictor variables in which we’re interested that potentially affects an outcome variable.
Confounding variable
evidence that the content of a test corresponds to the content of the construct it was designed to cover.
Content validity
a variable that can be measured to any level of precision. (Time is a continuous variable, because there is in principle no limit on how finely it could be measured.)
Continuous variable
a form of research in which you observe what naturally goes on in the world without directly interfering with it. This term implies that data will be analysed so as to look at relationships between naturally occurring variables rather than making statements about cause and effect. Compare with cross-sectional research, longitudinal research and experimental research.
Correlational research
a process of systematically varying the order in which experimental conditions are conducted. In the simplest case of there being two conditions (A and B), counterbalancing simply implies that half of the participants complete condition A followed by condition B, whereas the remainder do condition B followed by condition A. The aim is to remove systematic bias caused by practice effects or boredom effects.
Counterbalancing
evidence that scores from an instrument correspond with (concurrent validity) or predict (predictive validity) external measures conceptually related to the measured construct.
Criterion validity
a form of research in which you observe what naturally goes on in the world without directly interfering with it, by measuring several variables at a single time point. In psychology, this term usually implies that data come from people at different age points, with different people representing each age point. See also correlational research, longitudinal research.
Cross-sectional research
another name for outcome variable. This name is usually associated with experimental methodology (which is the only time it really makes sense) and is used because it is the variable that is not manipulated by the experimenter and so its value depends on the variables that have been manipulated.
Dependent variable
the difference between the observed value of a variable and the value of that variable predicted by a statistical model.
Deviance
evidence that the results of a study, experiment or test can be applied, and allow inferences, to real-world conditions.
Ecological validity
a form of research in which one or more variables are systematically manipulated to see their effect (alone or in combination) on an outcome variable. This term implies that data will be able to be used to make statements about cause and effect. Compare with cross-sectional research and correlational research.
Experimental research
the act of disproving a hypothesis or theory.
Falsification
a graph plotting values of observations on the horizontal axis, and the frequency with which each value occurs in the data set on the vertical axis (a.k.a. histogram).
Frequency distribution
a prediction about the state of the world (see experimental hypothesis and null hypothesis).
Hypothesis
an experimental design in which different treatment conditions utilize different organisms (e.g., in psychology, this would mean using different people in different treatment conditions) and so the resulting data are independent (a.k.a. between-groups or between-subjects design).
Independent design
another name for a predictor variable. This name is usually associated with experimental methodology (which is the only time it makes sense) and is used because it is the variable that is manipulated by the experimenter and so its value does not depend on any other variables (just on the experimenter). I just use the term predictor variable all the time because the meaning of the term is not constrained to a particular methodology.
Independent variable
the limits within which the middle 50% of an ordered set of observations fall. It is the difference between the value of the upper quartile and lower quartile.
Interquartile range
data measured on a scale along the whole of which intervals are equal. For example, people’s ratings of this book on Amazon.com can range from 1 to 5; for these data to be interval it should be true that the increase in appreciation for this book represented by a change from 3 to 4 along the scale should be the same as the change in appreciation represented by a change from 1 to 2, or 4 to 5.
Interval variable
this measures the degree to which scores cluster in the tails of a frequency distribution. There are different ways to estimate kurtosis and in SPSS no kurtosis is expressed as 0 (but be careful because outside of SPSS no kurtosis is sometimes a value of 3). A distribution with positive kurtosis (leptokurtic, kurtosis > 0) has too many scores in the tails and is too peaked, whereas a distribution with negative kurtosis (platykurtic, kurtosis < 0) has too few scores in the tails and is quite flat.
Kurtosis
the relationship between what is being measured and the numbers obtained on a scale.
Levels of measurement
a form of research in which you observe what naturally goes on in the world without directly interfering with it by measuring several variables at multiple time points. See also correlational research, cross-sectional research.
Longitudinal research
the value that cuts off the lowest 25% of the data. If the data are ordered and then divided into two halves at the median, then the lower quartile is the median of the lower half of the scores.
Lower quartile
a simple statistical model of the centre of a distribution of scores. A hypothetical estimate of the ‘typical’ score.
Mean
the discrepancy between the numbers used to represent the thing that we’re measuring and the actual value of the thing we’re measuring (i.e., the value we would get if we could measure it directly).
Measurement error
the middle score of a set of ordered observations. When there is an even number of observations the median is the average of the two scores that fall either side of what would be the middle value.
Median
the most frequently occurring score in a set of data.
Mode
description of a distribution of observations that has more than two modes.
Multimodal
where numbers merely represent names. For example, the numbers on sports players’ shirts: a player with the number 1 on her back is not necessarily worse than a player with a 2 on her back. The numbers have no meaning other than denoting the type of player (full back, centre-forward, etc.).
Nominal variable
a type of quantile; they are values that split the data into nine equal parts. They are commonly used in educational research.
Nonile
a probability distribution of a random variable that is known to have certain properties. It is perfectly symmetrical (has a skew of 0), and has a kurtosis of 0.
Normal distribution
data that tell us not only that things have occurred, but also the order in which they occurred. These data tell us nothing about the differences between values. For example, gold, silver and bronze medals are ordinal: they tell us that the gold medallist was better than the silver medallist, but they don’t tell us how much better (was gold a lot better than silver, or were gold and silver very closely competed?).
Ordinal variable
a variable whose values we are trying to predict from one or more predictor variables.
Outcome variable
a type of quantile; they are values that split the data into 100 equal parts.
Percentiles
refers to the possibility that participants’ performance in a task may be influenced (positively or negatively) if they repeat the task because of familiarity with the experimental situation and/or the measures being used.
Practice effect
a form of criterion validity where there is evidence that scores from an instrument predict external measures (recorded at a different point in time) conceptually related to the measured construct.
Predictive validity
a variable that is used to try to predict values of another variable known as an outcome variable.
Predictor variable
the function that describes the probability of a random variable taking a certain value. It is the mathematical function that describes the probability distribution.
Probability density function (PDF)
a curve describing an idealized frequency distribution of a particular variable from which it is possible to ascertain the probability with which specific values of that variable will occur. For categorical variables it is simply a formula yielding the probability with which each category occurs.
Probability distribution
extrapolating evidence for a theory from what people say or write (cf. quantitative methods).
Qualitative methods
inferring evidence for a theory through measurement of variables that produce numeric outcomes (cf. qualitative methods).
Quantitative methods
values that split a data set into equal portions.
Quantiles
a generic term for the three values that cut an ordered data set into four equal parts. The three quartiles are known as the lower quartile, the second quartile (or median) and the upper quartile.
Quartiles
the process of doing things in an unsystematic or random way. In the context of experimental research the word usually applies to the random assignment of participants to different treatment conditions.
Randomization
the value of the smallest score subtracted from the highest score. It is a measure of the dispersion of a set of scores. See also variance, standard deviation, and interquartile range.
Range
an interval variable but with the additional property that ratios are meaningful.
Ratio variable
the ability of a measure to produce consistent results when the same entities are measured under different conditions.
Reliability
an experimental design in which different treatment conditions utilize the same organisms (i.e., in psychology, this would mean the same people take part in all experimental conditions) and so the resulting data are related (a.k.a. related design or within-subject design).
Repeated-measures design
a measure of the symmetry of a frequency distribution. Symmetrical distributions have a skew of 0. When the frequent scores are clustered at the lower end of the distribution and the tail points towards the higher or more positive scores, the value of skew is positive. Conversely, when the frequent scores are clustered at the higher end of the distribution and the tail points towards the lower more negative scores, the value of skew is negative.
Skew
an estimate of the average variability (spread) of a set of data measured in the same units of measurement as the original data. It is the square root of the variance.
Standard deviation
variation due to some genuine effect (be it the effect of an experimenter doing something to all of the participants in one sample but not in other samples, or natural variation between sets of variables). We can think of this as variation that can be explained by the model that we’ve fitted to the data.
Systematic variation
another name for the sum of squares.
Sum of squared errors
the possibility that an apparent relationship between two variables is actually caused by the effect of a third variable on them both (often called the third-variable problem).
Tertium quid
the ability of a measure to produce consistent results when the same entities are tested at two different points in time.
Test-retest reliability
a hypothesized general principle or set of principles that explain known findings about a topic and from which new hypotheses can be generated.
Theory
this is variation that isn’t due to the effect in which we’re interested (so could be due to natural differences between people in different samples such as differences in intelligence or motivation). We can think of this as variation that can’t be explained by whatever model we’ve fitted to the data.
Unsystematic variation
the value that cuts off the highest 25% of ordered scores. If the scores are ordered and then divided into two halves at the median, it is the median of the top half of the scores.
Upper quartile
evidence that a study allows correct inferences about the question it was aimed to answer or that a test measures what it set out to measure conceptually (see also Content validity, Criterion validity).
Validity
anything that can be measured and can differ across entities or across time.
Variables
an estimate of average variability (spread) of a set of data. It is the sum of squares divided by the number of values on which the sum of squares is based minus 1.
Variance
another name for a repeated-measures design.
Within-subject design
the value of an observation expressed in standard deviation units. It is calculated by taking the observation, subtracting from it the mean of all observations, and dividing the result by the standard deviation of all observations. By converting a distribution of observations into these, a new distribution is created that has a mean of 0 and a standard deviation of 1.
z-score
