Correlational finding on Happiness and Ethnic status in the USA
Subject code: E04ab03t

StudyCsikszentmihalyi & Hunter (2003): study US 1998
TitleHappiness in Everyday Life: the Uses of Experience Sampling.
SourceJournal of Happiness Studies, 2003, Vol. 4, 185 - 199
PublicTeenagers, USA, 199?
SampleNon-probability purposive sample
Respondents N =828

Author's labelEthnicity
Page in Source 192
Our classificationEthnic status in the USA, code E04ab03t
a: African American
b: Asian American
c: Caucasian
d: Hispanic

Observed Relation with Happiness
a, d > b, c (Africans and hispanics feel happier)

Participants were beeped at random moments eight 
times a day from 7:30 am to 10:0 pm for one week. 
At each beep they answered questions about:
a: what activity they where doing on the moment
b: whom they were with 
c: how they felt at that moment (various feelings, 
one of which happiness)
A-ARE-mi-sqr-n-7-aAoV= ns
ANOVA controlling SES

Appendix 1: Happiness measures used
CodeFull Text
A-ARE-mi-sqr-n-7-aSelfreport on single question repeated several times a day.

" .. mood .."
Full lead question not reported
7 happy
1 sad

Appendix 2: Statistics used
Type: statistical procedure
Measurement level: Correlate(s): nominal, Happiness: metric.
In an ANOVA, the total happiness variability, expressed as the sum of squares, is split into two or more parts, each of which is assigned to a source of variability. At least one of those sources is the variability of the correlate, in case there is only one, and always one other is the residual variability, which includes all unspecified influences on the happiness variable. Each sum of squares has its own number of degrees of freedom (df), which sum up to Ne -1 for the total variability. If a sum of squares (SS) is divided by its own number of df, a mean square (MS) is obtained. The ratio of two correctly selected mean squares has an F-distribution under the hypothesis that the corresponding association has a zero-value.

NOTE: A significantly high F-value only indicates that, in case of a single correlate, the largest of the c mean values is systematically larger than the smallest one. Conclusions about the other pairs of means require the application of a Multiple Comparisons Procedure (see e.g. BONFERRONI's MULTIPLE COMPARISON TEST, DUNCAN's MULTIPLE RANGE TEST or STUDENT-NEWMAN-KEULS)
Type: descriptive statistic only.
Measurement level: Correlate level: dichotomous, but nominal or ordinal theoretically possible as well. Happiness level: dichotomous
Range: [-100; +100]

Meaning: the difference of the percentages happy people at two correlate levels.
Ruut Veenhoven, World Database of Happiness, Collection of Correlational Findings, Erasmus University Rotterdam.