Editing Finding relations between variables in time series
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Most personal science projects require finding relationships between different variables of the type 'time series'<ref>Core-Guide_Longitudinal-Data-Analysis_10-05-17.pdf (duke.edu)</ref>. An example could be the question "does my daily chocolate consumption correlate with my daily focus score?". | Most personal science projects require finding relationships between different variables of the type 'time series'<ref>Core-Guide_Longitudinal-Data-Analysis_10-05-17.pdf (duke.edu)</ref>. An example could be the question "does my daily chocolate consumption correlate with my daily focus score?". | ||
− | You could do experiments if you control everything rigidly or if the effects are strong and quick, like less than a week. Old data may be useable as Baseline | + | You could do experiments if you control everything rigidly or if the effects are strong and quick, like less than a week. Old data may be useable as Baseline. If both block (like 2 weeks) and daily mixed (random intervention every day) produce the same results then issues of time series are probably not in your experiment. |
Finding more complicated relationships require better statistical tests and algorithms and data science skills. Apps that would do this automatically or at least easily are not yet available. See below. Most internet resources treat time series as (regular cyclical) series, which is not useful as most of the tracked variables have irregular patterns and don't even have a regularly cyclical component. | Finding more complicated relationships require better statistical tests and algorithms and data science skills. Apps that would do this automatically or at least easily are not yet available. See below. Most internet resources treat time series as (regular cyclical) series, which is not useful as most of the tracked variables have irregular patterns and don't even have a regularly cyclical component. |