For most, Shame is generally lowest after an average of 1.7 millimeters of Precipitation over the previous 7 days.
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People with higher Precipitation usually have higher Shame
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Precipitation on each day of the week.
This chart shows the typical value recorded for Precipitation for each month of the year.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Shame on each day of the week.
This chart shows the typical value recorded for Shame for each month of the year.

Abstract

Aggregated data from 45 study participants suggests with a medium degree of confidence (p=0.21833963880063, 95% CI -0.466 to 0.441) that Precipitation has a very weakly negative predictive relationship (R=-0.01) with Shame. The highest quartile of Shame measurements were observed following an average 9 millimeters Precipitation. The lowest quartile of Shame measurements were observed following an average 2.0878246365604 mm Precipitation.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Precipitation and Shame. Additionally, we attempt to determine the Precipitation values most likely to produce optimal Shame values.

Participant Instructions

Grant access to your weather and air quality data on the Import Data page. Your data will automatically be imported and analyzed.
Record your Shame daily in the reminder inbox or using the interactive web or mobile notifications.

Design

This study is based on data donated by 45 participants. Thus, the study design is equivalent to the aggregation of 45 separate n=1 observational natural experiments.

Data Analysis

Precipitation Pre-Processing
Precipitation measurement values below 0 millimeters were assumed erroneous and removed. No maximum allowed measurement value was defined for Precipitation. No missing data filling value was defined for Precipitation so any gaps in data were just not analyzed instead of assuming zero values for those times.
Precipitation Analysis Settings

Shame Pre-Processing
Shame measurement values below 1 out of 5 were assumed erroneous and removed. Shame measurement values above 5 out of 5 were assumed erroneous and removed. No missing data filling value was defined for Shame so any gaps in data were just not analyzed instead of assuming zero values for those times.
Shame Analysis Settings

Predictive Analytics
It was assumed that 0 hours would pass before a change in Precipitation would produce an observable change in Shame. It was assumed that Precipitation could produce an observable change in Shame for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Sources

Precipitation data was primarily collected using Weather. Automatically import temperature, humidity, hours of daylight, air quality and pollen count.

Shame data was primarily collected using QuantiModo. QuantiModo allows you to easily track mood, symptoms, or any outcome you want to optimize in a fraction of a second. You can also import your data from over 30 other apps and devices. QuantiModo then analyzes your data to identify which hidden factors are most likely to be influencing your mood or symptoms.

Limitations

As with any human experiment, it was impossible to control for all potentially confounding variables. Correlation does not necessarily imply correlation. We can never know for sure if one factor is definitely the cause of an outcome. However, lack of correlation definitely implies the lack of a causal relationship. Hence, we can with great confidence rule out non-existent relationships. For instance, if we discover no relationship between mood and an antidepressant this information is just as or even more valuable than the discovery that there is a relationship.
We can also take advantage of several characteristics of time series data from many subjects to infer the likelihood of a causal relationship if we do find a correlational relationship. The criteria for causation are a group of minimal conditions necessary to provide adequate evidence of a causal relationship between an incidence and a possible consequence.

The list of the criteria is as follows:
Strength (A.K.A. Effect Size)
A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal. There is a very weakly negative relationship between Precipitation and Shame

Consistency (A.K.A. Reproducibility)
Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect. Furthermore, in accordance with the law of large numbers (LLN), the predictive power and accuracy of these results will continually grow over time. 60 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Precipitation values, the observed strength of the relationship will decline until it is below the threshold of significance. To it another way, in the case that we do find a spurious correlation, suggesting that banana intake improves mood for instance, one will likely increase their banana intake. Due to the fact that this correlation is spurious, it is unlikely that you will see a continued and persistent corresponding increase in mood. So over time, the spurious correlation will naturally dissipate.

Specificity
Causation is likely if a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.

Temporality
The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay). The confidence in a causal relationship is bolstered by the fact that time-precedence was taken into account in all calculations.

Biological Gradient
Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.

Plausibility
A plausible bio-chemical mechanism between cause and effect is critical. This is where human brains excel. Based on our responses so far, 1 humans feel that there is a plausible mechanism of action and 0 feel that any relationship observed between Precipitation and Shame is coincidental.

Coherence
Coherence between epidemiological and laboratory findings increases the likelihood of an effect. It will be very enlightening to aggregate this data with the data from other participants with similar genetic, diseasomic, environmentomic, and demographic profiles.

Experiment
All of human life can be considered a natural experiment. Occasionally, it is possible to appeal to experimental evidence.

Analogy
The effect of similar factors may be considered.

Relationship Statistics

Property Value
Cause Variable Name Precipitation
Effect Variable Name Shame
Sinn Predictive Coefficient 0.0055059356080393
Confidence Level medium
Confidence Interval 0.45346033219937
Forward Pearson Correlation Coefficient -0.0124
Critical T Value 1.6897977777778
Average Precipitation Over Previous 7 days Before ABOVE Average Shame 9 millimeters
Average Precipitation Over Previous 7 days Before BELOW Average Shame 2.0878246365604 millimeters
Duration of Action 7 days
Effect Size very weakly negative
Number of Paired Measurements 60
Optimal Pearson Product 0.14513125381458
P Value 0.21833963880063
Statistical Significance 0.32322444468737
Strength of Relationship 0.45346033219937
Study Type population
Analysis Performed At 2019-01-29
Number of Participants 45

Precipitation Statistics

Property Value
Variable Name Precipitation
Aggregation Method MEAN
Analysis Performed At 2019-01-27
Duration of Action 7 days
Kurtosis 55.837468890152
Mean 1.9130805084337 millimeters
Median 0.41915017211704 millimeters
Minimum Allowed Value 0 millimeters
Number of Correlations 203
Number of Measurements 1211238
Onset Delay 0 seconds
Standard Deviation 4.171951057237
Unit Millimeters
UPC 721866373106
Variable ID 5954746
Variance 29.482937133789

Shame Statistics

Property Value
Variable Name Shame
Aggregation Method MEAN
Analysis Performed At 2019-01-18
Duration of Action 24 hours
Kurtosis 3.5382186707826
Maximum Allowed Value 5 out of 5
Mean 2.2145381017882 out of 5
Median 2.1500402432658 out of 5
Minimum Allowed Value 1 out of 5
Number of Correlations 307
Number of Measurements 20668
Onset Delay 0 seconds
Standard Deviation 0.62734560754172
Unit 1 to 5 Rating
Variable ID 1443
Variance 0.67641801665658

https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn