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This individual's Guiltiness is generally lowest after a daily total of 120 minutes of Played Guitar over the previous 7 days.
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Blue represents the sum of Played Guitar over the previous 7 days
An increase in 7 days cumulative Played Guitar is usually followed by an decrease in Guiltiness. (R = -0.025)
Typical values for Guiltiness following a given amount of Played Guitar over the previous 7 days.
Typical Played Guitar seen over the previous 7 days preceding the given Guiltiness value.
This chart shows how your Played Guitar changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Played Guitar on each day of the week.
This chart shows the typical value recorded for Played Guitar for each month of the year.
This chart shows how your Guiltiness changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Guiltiness on each day of the week.
This chart shows the typical value recorded for Guiltiness for each month of the year.

Abstract

This individual's Guiltiness is generally 2% lower than normal after 120 minutes Played Guitar per 7 days. This individual's data suggests with a high degree of confidence (p=0.23496737066905, 95% CI -0.149 to 0.099) that Played Guitar has a very weakly negative predictive relationship (R=-0.03) with Guiltiness. The highest quartile of Guiltiness measurements were observed following an average 92 minutes Played Guitar per day. The lowest quartile of Guiltiness measurements were observed following an average 1.6275510204082 h Played Guitar per day.Guiltiness is generally 2% lower than normal after a total of 98 minutes of Played Guitar over the previous 7 days. Guiltiness is generally 2% higher after a total of 92 minutes of Played Guitar over the previous 7 days.

Objective

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

Participant Instructions

Record your Played Guitar daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Guiltiness daily in the reminder inbox or using the interactive web or mobile notifications.

Design

This study is based on data donated by one participant. Thus, the study design is consistent with an n=1 observational natural experiment.

Data Analysis

Played Guitar Pre-Processing
Played Guitar measurement values below 0 seconds were assumed erroneous and removed. Played Guitar measurement values above 7 days were assumed erroneous and removed. It was assumed that any gaps in Played Guitar data were unrecorded 0 seconds measurement values.
Played Guitar Analysis Settings

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

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Played Guitar would produce an observable change in Guiltiness. It was assumed that Played Guitar could produce an observable change in Guiltiness for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
424 raw Played Guitar measurements with 153 changes spanning 669 days from 2017-06-01 to 2019-04-01 were used in this analysis. 2793 raw Guiltiness measurements with 661 changes spanning 1961 days from 2013-11-17 to 2019-04-01 were used in this analysis.

Data Sources

Played Guitar 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.

Guiltiness 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 causation. 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 Played Guitar and Guiltiness

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. 501 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Played Guitar 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 Played Guitar and Guiltiness 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 Played Guitar
Effect Variable Name Guiltiness
Sinn Predictive Coefficient 0.0249
Confidence Level high
Confidence Interval 0.12362081272998
Forward Pearson Correlation Coefficient -0.025
Critical T Value 1.646
Total Played Guitar Over Previous 7 days Before ABOVE Average Guiltiness 92 minutes
Total Played Guitar Over Previous 7 days Before BELOW Average Guiltiness 98 minutes
Duration of Action 7 days
Effect Size very weakly negative
Number of Paired Measurements 501
Optimal Pearson Product 0.0017357583989364
P Value 0.23496737066905
Statistical Significance 0.9977
Strength of Relationship 0.12362081272998
Study Type individual
Analysis Performed At 2019-04-04

Played Guitar Statistics

Property Value
Variable Name Played Guitar
Aggregation Method SUM
Analysis Performed At 2019-04-01
Duration of Action 7 days
Kurtosis 2.6923341571819
Maximum Allowed Value 7 days
Mean 13 minutes
Median 0 seconds
Minimum Allowed Value 0 seconds
Number of Changes 153
Number of Correlations 178
Number of Measurements 424
Onset Delay 30 minutes
Standard Deviation 0.27556923932731
Unit Hours
Variable ID 5968689
Variance 0.075938405663433

Guiltiness Statistics

Property Value
Variable Name Guiltiness
Aggregation Method MEAN
Analysis Performed At 2019-04-01
Duration of Action 24 hours
Kurtosis 3.1224153723756
Maximum Allowed Value 5 out of 5
Mean 2.1627 out of 5
Median 2 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 661
Number of Correlations 5379
Number of Measurements 2793
Onset Delay 0 seconds
Standard Deviation 0.92130141512025
Unit 1 to 5 Rating
Variable ID 1335
Variance 0.84879629750257

Tracking Played Guitar

Record your Played Guitar daily in the reminder inbox or using the interactive web or mobile notifications.

Tracking Guiltiness

Record your Guiltiness daily in the reminder inbox or using the interactive web or mobile notifications.
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https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn