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Chapter 10

# PSYB01 Chapter 10 exam prep- key terms.doc

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University of Toronto Scarborough

Psychology

PSYB01H3

David Nussbaum

Fall

Description

Chapter 10: Quantitative Data Analysis
Key Terms
Term Page Definition
Bar Chart 319 A graphic for qualitative variables in which the variable's
distribution is displayed with solid bars separated by spaces
Between- 338 Calculated by comparing the difference of each of the means of
groups the individual groups with the overall or grans mean for all scores
Variance in the experiment; the between-groups variance represents
systematic variance due to the manipulation of the independent
variable
Bimodal 323 A distribution that has two nonadjacent categories with about the
same number of cases, and these categories have more cases
than any others
Central 322 The most common value (for variables measured at the nominal
tendency level) or the value around which cases tend to center (for a
quantitative variable)
Chi-square 343 An inferential statistic used to test hypotheses about relationships
(X^2) test between two or more categorical variables in a contingency table
of
independen
ce
Contingenc 342 A bivariate (two variable) or higher order distribution showing the
y table distribution of one variable for each category of another variable.
Also called cross tabulation. Often used with chi-square (X^2) test
of independence to tabulate and analyze relationship between
two or more categorical variables
Correlation 000 A statistic that measures the extent to which two variables are
associated but not necessarily causally related
Critical t- 335 The value that the t-statistic must exceed in order to reject the
value null hypothesis at a certain level of probability
Degrees of 336 In tests of statistical significance, the number of observation that
freedom are free to vary in estimating a population parameter
Descriptive 314 Statistics used to describe the distribution of and relationship
statistics among variables, usually in the form of averages and standard
deviations (a statistical measure of variability)
Effect size 342 A standardized measure of association; often the difference
between the mean of the experimental group and the mean of the
control group on the dependent variable, adjusted for the average
variability in the two groups. The effect size measures the
strength of the predicted or hypothesized relationship between
the independent variable and dependent variable
f-test 334 ANOVA computes an f-statistic, which is the ratio of two types of
variance: systematic and error variance
Frequency 316 Numerical display showing the number of cases, and usually the distribution percentage of case (the relative frequencies), corresponding to
each value or group of values of a variable
Histogram 320 A graphic for quantitative variables in which the variable's
distribution is displayed with adjacent bars
Inferential 315 A mathematical tool for estimating how likely it is that a statistical
statistics result based on data from a random sample is representative of
the population from which the sample is assumed to have been
selected
Mean 323 The arithmetic, or weighted, average, computed by adding up the
value of all the cases and dividing by the total number of cases
Median 323 The position average, or the point that divides a distribution in
half (the 50th percentile)
Mode 338 The most frequent value is a distribution; also termed the
probability average
Multifactor 338 Used for experimental designs with more than one factor or
ANOVA independent variable varied simultaneously. In comparison to the
simple ANOVA, the multifactor ANOVA is much more
computationally complex given that there are both main and
interaction effects that need to be tested
Normal 332 Refer to normal curve
Distribution
Null 333 The hypothesis of no differences or no relationship, which the
hypothesis researcher tries to reject, nullify, or disprove
One-factor 337 Refer to simple ANOVA
ANOVA
One-tailed 335 In order to reject the null hypothesis, the value of the test statistic
test

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