LESSON 3 Flashcards
no systematic relationship between two variables
No correlation
relation between two variables that shows up on a scatter diagram as dots following a systematic pattern thatis not a straightline(Aron et al., 2013)
Curvilinear correlation
relation between two variables that shows up on a scatter diagram as the dots roughly following a straightline
Linear correlation
a nonparametric measure of the strength and direction of association that exists between two variables measured on at least an ordinal scale
Spearman’s RHO (rs)
• to determine the statistical significance of the r, convert it into t score and check the critical value from the ttable
alternatively
• you can also use the rtable
Significance of the r
also called Pearson’s r, devised by Karl Pearson, is a
measure of the STRENGTH of a LINEAR ASSOCIATION between two variables
Pearson product -moment correlation
TECHNIQUE also known as bivariate correlation, is a STATISTICAL technique that is used to measure and describe the relationship between two
variables
Correlation
Used to transpose raw scores from a college or graduate school admission test
M= 500; SD=100
GRE/SAT
are different from other standard scores in that they take on whole values from 1 to 9, which
represent a range of performance that is half of a standard deviation in width
M= 5; SD = 2
Stanine/ standard nine
indicate how many standard deviation units an examinee’s score is above or below the mean
M= 50; SD = 10
T-score
results from the conversion of a raw score into a number indicating how many standard deviation units
the raw score is below or above the mean of the distribution
M= 0; SD = 1
Z-score
square root of the average of the squared deviations from the mean; the most common descriptive statistics for variation (√)
Standard deviation
the difference between a score and the mean
Deviation or deviation score
measure of how spread out a set of scores are; average of the squared deviations from the mean (Aron et al., 2013)
Variance
distance covered by the scores in a distribution, from the smallest score to the largest score (Gravetter et al., 2020)
Range=Xmax-Xmin
Range
provides a QUANTITATIVE measure of the DIFFERENCE between scores in a distribution and DESCRIBES the degree to which the scores are spread out or clustered together
(Gravetter et al., 2020)
Variability
___ the scores are concentrated towards the mean
___ – normal curve
___ – the scores have an extremely large
deviation from the mean]
Leptokurtic
Mesokurtic
Platykurtic
extent to which a frequency distribution deviates
from a normal curve in terms of whether its curve in
the middle is more peaked or flat than the normal
curve.
Kurtosis
specific, mathematically defined, bell-shaped
frequency distribution that is symmetrical and
unimodal
Normal distribution
situation in which many scores pile up atthe high end of a distribution (creating a
skewness to the left) because itis not possible to
have a higher score. (Aron et al., 2013
Negatively skewed distribution
Ceiling effect
the peak (highestfrequency) in the distribution is on
the left /-hand side with the tail tapering on the RIGHT
- The majority of scores is below the average
- Floor effect
Positively skewed distribution
– situation in which many scores pile up atthe low end of a distribution (creating a skewness to the right) because itis not possible to have any
lower score (Aron et al., 2013)
Positively skewed distribution
Floor effect
distribution in which the pattern of frequencies on
the left and right side are mirrorimages of each
other(Aron et al., 2013)
Symmetrical distribution
frequency distribution with two or more high frequencies separated by a lowerfrequency (Aron et al., 2013)
Multimodal distribution
