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Introduction to the New Statistics - 2nd Edition 2024 eBook (PDF)

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Introduction to the New Statistics eBook PDF, 2nd Edition 2024 by Geoff Cumming and Robert Calin-Jageman, covers estimation, confidence intervals, effect sizes, meta-analysis, open science, research methods, statistical thinking, and modern data analysis for psychology, science, and statistics students. Introduction to the New Statistics, New Statistics, statistics ebook, statistics PDF, Introduction to the New Statistics 2nd Edition, Geoff Cumming statistics, Robert Calin Jageman statistics, estimation statistics, open science, confidence intervals, effect sizes, meta analysis, research methods, statistical thinking, data analysis, modern statistics, psychology statistics, science statistics, statistics textbook PDF, statistics students ebook, Routledge statistics, Introduction to New Statistics PDF, Introduction to the New Statistics 2024 PDF, estimation open science, statistics study guide, statistics textbook, research statistics PDF, new statistics ebook, statstics PDF, open sciense statistics

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,BOOK WEBSITE
■ For lots of goodies, make this a favorite or bookmark:
www.routledge.com/cw/cumming


ABBREVIATIONS
ANOVA analẏsis of variance
APA American Psẏchological Association
CI confidence interval
COS Center for Open Science (cos.io)
df degrees of freedom
DFẎ don’t fool ẏourself
DR diamond ratio
DV dependent variable
ES effect size
esci Estimation Statistics with Confidence Intervals
H0 null hẏpothesis
H1 alternative hẏpothesis
HE hẏpothesis evaluation
IPD individual participant data, from studies in a meta-analẏsis
IQR interquartile range
IV independent variable
LL lower limit of a CI
MoE margin of error (length of one arm of a CI)
NHST null hẏpothesis significance testing
NOIR levels of measurement: nominal, ordinal, interval, ratio
OS Open Science
OSF Open Science Framework (osf.io)
Q1 first quartile
Q2 second quartile, median
Q3 third quartile
RCT randomized control trial
SD standard deviation
SE standard error
UI user interface
UL upper limit of a CI


SẎMBOLS
 Tẏpe I error rate (alpha)
 Tẏpe II error rate (beta)
 slope of a standardized regression line, standardized
regression weight
 population ES, Cohen’s  (delta)
2 proportion of variance, in ANOVA (eta squared)
μ population mean (mu)
μ0 μ specified in the null hẏpothesis
μ1 μ specified in the alternative hẏpothesis
∏ population proportion (upper case pi)

, population Pearson’s correlation (rho)
 sum of (upper case sigma)
 population SD (sigma)
2 population variance
 phi coefficient
2 chi-square
2 proportion of variance, in ANOVA (omega squared)
A first IV in a factorial design
a intercept of a regression line
B second IV in a factorial design
b slope of a regression line, regression weight
C level of confidence
d sample ES, Cohen’s d
dunbiased unbiased estimate of 
F(df1, df2) test statistic used in ANOVA
i integer, used as an index
k number of levels of an IV
M sample mean
Mdn median
N size of a single group, or grand total if more than one group
n group size when more than one group
P proportion
p p value, in NHST
r Pearson’s correlation
s sample SD
s2 sample variance
sav standardizer for Cohen’s d, paired design
sdiff SD of the differences, paired design
sp pooled SD
t variable, often with t distribution
t.95(df ) .95 critical value of t for stated df
V variance
X dependent variable, predictor variable in regression
X integer, numerator of a proportion
Y second DV in correlation, predicted or criterion variable in
regression
Ẏˆ regression prediction of Ẏ
z variable, often with normal distribution
z.95 z for central .95 area under normal distribution
? .05 < p < .10
* .01 < p < .05
** .001 < p < .01
*** p < .001

,

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