Week 2 Flashcards
Dependent variable
A variable (often y) whose value depends on that of another. “Effect”
Independent variable
Variable (often x) whose variation does not depend on that of another. “Cause”
Confounds
Things that are going to interrupt your experiment.
Research question
Addresses theory using a general question. More general than hypothesis.
Hypothesis
Tentative statement derived from theory that specifies a relationship between specific concepts in form of prediction.
Operationalise
Explicitly defining a way to measure something. Ie how to measure emotional intelligence
Epistemological framework
How you conceptualise knowledge about the world.
Basic research
Tries to answer basic/fundamental questions about the nature of behaviour. Doesn’t seek to solve problems. Based on curiosity.
Lexicon
Mental dictionary
Applied research
Conducted to address issues in which there are practical problems and potential solutions. Takes place in real world.
Inter rater reliability
Getting another person to co-rate observations/data
Extraneous variables
Any variable other than IV that could affect the dependent variable
Normal distribution
A histogram that looks the same on both sides if a line is drawn down the centre. Majority of scores lie around the centre. Kurtosis and and skew are 0.
Skew
Not a symmetrical distribution. Tall bars of graph clustered at one end of scale.
Positive skew
Frequent scores clustered at lower end with tail pointing towards higher more positive scores
Negative skew
Frequent scores clustered at higher end with tail pointing towards lower more negative score.
Kurtosis
Degree to which scores cluster at the ends of the distribution (the tails). How pointy a distribution is.
Positive kurtosis (leptokurtic)
Many scores in the tails (heavy distribution)
Negative kurtosis (platykurtic)
Thin tails and flatter than normal.
Central tendency M(italics) or X
Centre of a frequency distribution
Mode
Score that occurs most frequently in the data. Can be more than one I.e. Bimodal, multi modal
Median Mdn(italics)
Middle score when scores are ranked in order of magnitude. Calculated differently for odd and even # of scores
Mean
Measure of central tendency. Add up all scores and \ by total # of scores. Can be influenced by extreme scores.
Range of scores
Taking largest score and subtracting it from the smallest.
Interquartile range IQR
Cut off top and bottom 25% of scores and calculate the middle 50% scores.
Quartiles
3 values that split the sorted data into 4 equal parts.
2nd quartile
Median - data is in 2 equal parts
Lower quartile
Median of the lower half of data
Upper quartile
Median of the upper half of data
Quantile
Values that split the data into 4 equal portions.
Percentiles
Points that split data into 100 equal parts
Noniles
Points that split data into 9 equal parts.
Deviance
Difference between each score and the mean
Sum of squares
Adding up of squared deviances. Indicates total dispersion/total deviance of scores from the mean.
Standard deviation
The squared root of the variance. Variance is the mean of the sum of squares. As SD gets larger distribution gets fatter.
Small SD
Indicates that data points are close to the mean.
Large SD
Data points are distant from the mean.
Z score
Take each score and subtract it from the mean of all scores. Then divide by the SD. Used to calculate probability.
N
Entire sample
n
Subsample I.e. # of cases within a particular group
