Summary
Summary statistics Field (English) Ch. 3, 6, 8-9, 11-13, 15
- Course
- Institution
- Book
This summary covers all aspects that were discussed (and you will be tested on) during the 4.4C AMDA course.
[Show more]
Connected book
Book Title:
Author(s):
- Edition:
- ISBN:
- Edition:
More summaries for
-
Exam Guide for Applied Multivariate Data Analysis – Get yourself a Wonderful Grade!
-
Summary of Statistics (IBC), Radboud University
-
Answers assignment 3 business research methods
Seller
Follow
NienkeRaaijmakers
Reviews received
Content preview
Field summary (5th ed.)Chapter 3: NHST and effect sizes p. 3
NHST
researcher degrees of freedom
statistical significance
effect sizes: Cohen’s d and Pearson’s r
odds ratio
Chapter 6: Statistical bias p. 4
bias
outlier
violation of assumption: linearity and additivity, normality, homogeneity/homoscedasticity,
independence
trimming
winsorizing
bootstrapping
Chapter 8: Correlations p. 6
covariation
bivariate correlation
one-tailed and two-tailed probability
directional and non-directional hypothesis
point-biserial correlation and biserial correlation
discrete dichotomy and continuous dichotomy
semi-partial (part) correlation and partial correlation
Chapter 9: Linear regression model p. 8
single regression
predicted value
multiple regression
parameter
total error
residual sum of squares, SSR
goodness of fit
sum of squared differences, SST
proportion of improvement, R2
F-statistic
mean squares, MS
unstandardized residuals, standardized residuals, and studentized residuals
adjusted predicted value
Cook’s distance
leverage
Mahalanobis distance
multicollinearity, VIF, and tolerance
cross-validation
hierarchical regression
forced entry
,stepwise, forward and backward
F-change
eigenvalues
Chapter 11: Moderation, mediation, and multi-category predictors p. 12
moderation
grand mean centring
simple slopes analysis
zone of significance
mediation
simple relationship and mediated relationship
Chapter 12: Comparing several independent means p. 15
F-statistic
SST, SSM, dfM, SSR, MS, MSM, MSR
Welch’s F and Brown-Forsythe’s F
contrast coding
post hoc tests
weights for planned contrasts
grand mean
non-orthogonal contrasts
standard contrasts: deviation (first and last), simple (first and last), repeated, Helmert, difference
(reverse Helmert)
between-group effects table
within-group effects table
harmonic mean sample size
Chapter 13: ANCOVA p. 20
covariates
adjusted means
partial eta-squared
omega squared
Chapter 14: Factorial designs p. 22
independent factorial design (Ch. 14)
repeated-measures (related) factorial design (Ch. 15)
mixed design (Ch. 16)
slope interaction term
Chapter 15: Repeated-measures designs p. 25
random intercept model
sphericity and Mauchly’s test
Greenhouse-Geisser and Huynh-Feldt
lower-bound estimate of sphericity
SSw, dfSSW
MSM, MSR, and F
factorial repeated-measures design
Chapter 16: Mixed designs p. 28
mixed designs
, Chapter 3: NHST and effect sizes
Null hypothesis significance testing (NHST)
Tests H0 against Ha to see whether Ha is likely to be true. p is used as an index of the evidence weight
against H0.
Problem with NHST: reliance on merely refuting H0 (all-or-nothing thinking, with p<.05 or >.05)
Researcher degrees of freedom: showing results in the most favorable light possible (not
controlling the Type I error rate)
- p-hacking: selectively reporting significant p-values
- p-HARKing: hypothesizing after the results are known
Statistical significance
p = the probability of getting a test statistic at least as large as the one observed, relative to all
possible values of the test statistic from an infinite number of identical replications.
p doesn’t measure the size/importance of an effect, so don’t use p as the measure of probability
that the hypothesis in question is true/false
small p suggests data are compatible with Ha, large p suggests data are compatible with H0
Effect sizes
Effect sizes = objective and (usually) standardized measures of the magnitude of observed effects.
Standardized: allows to compare [effect sizes] across different studies that have measured different
variables/used different scales of measurement.
The size of the effect should be placed within the research context. However, rules of thumb are:
Cohen’s d Pearson’s r
small .2 .1 r=.1 explains 1% of total variance
medium .5 .3 r=.3 explains 9% of total variance
large .8 .8 (r=.5 explains 25% of total variance)
Cohen’s d: Calculated by dividing the difference between means by the standard deviation:
d = (mean1 – mean2)/s
expressed in s-units, therefore standardized, and more reliable than Pearson’s r when group sizes
are discrepant
Pearson’s correlation coefficient r: A measure of the strength of the relationship between 2 variables
(either continuous or one continuous and one categorical with two categories).
r is not linear, meaning r=60 is not 2x r=30. It is constrained to lie between 0 (no effect) and 1.
Odds ratio: Popular effect size for counts as an outcome (e.g. on 2 categorical variables) with outcome
being a number of participants choosing each option on the categorical variables).
count is summarized in a [2x2] contingency table
odds = pevent/pno event = pevent/total / pno event/total
odds = 1 indicates that the odds of one outcome are the same as odds for the other outcome
Effect sizes as an indication to NHST:
- interpreting effects on a continuum rather than a rule (of p < .05)
- affected by sample size, but without a decision rule attached (e.g. p < .05)
- due to absence of decision rule: less researcher degrees of freedom.
Effect sizes can be used in a meta-analysis as it gives the average effect size across studies: ∑effect
sizes/Neffect sizes
The benefits of buying summaries with Stuvia:
Guaranteed quality through customer reviews
Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.
Quick and easy check-out
You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.
Focus on what matters
Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!
Frequently asked questions
What do I get when I buy this document?
You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.
Satisfaction guarantee: how does it work?
Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.
Who am I buying these notes from?
Stuvia is a marketplace, so you are not buying this document from us, but from seller NienkeRaaijmakers. Stuvia facilitates payment to the seller.
Will I be stuck with a subscription?
No, you only buy these notes for $5.89. You're not tied to anything after your purchase.
Can Stuvia be trusted?
4.6 stars on Google & Trustpilot (+1000 reviews)
67474 documents were sold in the last 30 days
Founded in 2010, the go-to place to buy study notes for 14 years now