Subject code: L17ab04

Study | Csikszentmihalyi & Hunter (2003): study US 1998 |

Title | Happiness in Everyday Life: the Uses of Experience Sampling. |

Source | Journal of Happiness Studies, 2003, Vol. 4, 185 - 199 |

DOI | DOI:10.1023/A:1024409732742 |

Public | Teenagers, USA, 199? |

Sample | Non-probability purposive sample |

Non-Response | |

Respondents N = | 828 |

Correlate | |

Author's label | Social class of community |

Page in Source | 192,195 |

Our classification | Socio-economic status of vinicity, code L17ab04 |

Operationalization | 1 Poor 2 Working class 3 Middle class 4 Upper-middle class 5 Upper class |

Observed Relation with Happiness | ||

Happiness Measure | Statistics | Elaboration/Remarks |

A-ARE-mi-sqr-n-7-a | F=+8.1 p < .0001 | 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-a | AoV=-.08 p < .002 | ANOVA controlling for: - age - gender - SES - % time in flow |

Appendix 1: Happiness measures used

Code | Full Text |

A-ARE-mi-sqr-n-7-a | Selfreport on single question repeated several times a day. " .. mood .." Full lead question not reported 7 happy 6 5 4 3 2 1 sad |

Appendix 2: Statistics used

Symbol | Explanation |

AoV | ANALYSIS of VARIANCE (ANOVA) 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) |

F | F-STATISTIC Type: asymmetric standard test statistic. Range: nonnegative unlimited Meaning : the test statistic is also called the "Variance Ratio" and is the ratio of two independent estimators of the same variance with n1 and n2 degrees of freedom respectively. The critical values of its probability distribution are tabulated extensively in almost any textbook on Statistics |

Ruut Veenhoven, World Database of Happiness, Collection of Correlational Findings, Erasmus University Rotterdam.

https://worlddatabaseofhappiness.eur.nl