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This individual's Code Commits is generally highest after a daily total of 600 milligrams of CoQ10 By Doctors Best intake over the previous 7 days.
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Blue represents the sum of CoQ10 By Doctors Best intake over the previous 7 days
An increase in 7 days cumulative CoQ10 By Doctors Best intake is usually followed by an increase in Code Commits. (R = 0.266)
Typical values for Code Commits following a given amount of CoQ10 By Doctors Best intake over the previous 7 days.
Typical CoQ10 By Doctors Best intake seen over the previous 7 days preceding the given Code Commits value.
This chart shows how your CoQ10 By Doctors Best changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for CoQ10 By Doctors Best on each day of the week.
This chart shows the typical value recorded for CoQ10 By Doctors Best for each month of the year.
This chart shows how your Code Commits changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Code Commits on each day of the week.
This chart shows the typical value recorded for Code Commits for each month of the year.

Abstract

This individual's Code Commits is generally 32% higher than normal after a total of 600 milligrams CoQ10 By Doctors Best intake over the previous 7 days. This individual's data suggests with a high degree of confidence (p=3.841650593355E-14, 95% CI -6.096 to 6.628) that CoQ10 By Doctors Best has a weakly positive predictive relationship (R=0.27) with Code Commits. The highest quartile of Code Commits measurements were observed following an average 550.32 milligrams CoQ10 By Doctors Best per day. The lowest quartile of Code Commits measurements were observed following an average 298.93955461294 mg CoQ10 By Doctors Best per day.Code Commits is generally 30% lower than normal after a total of 298.93955461294 milligrams of CoQ10 By Doctors Best intake over the previous 7 days. Code Commits is generally 32% higher after a total of 550.32 milligrams of CoQ10 By Doctors Best intake over the previous 7 days.

Objective

The objective of this study is to determine the nature of the relationship (if any) between CoQ10 By Doctors Best and Code Commits. Additionally, we attempt to determine the CoQ10 By Doctors Best values most likely to produce optimal Code Commits values.

Participant Instructions

Record your CoQ10 By Doctors Best daily in the reminder inbox or using the interactive web or mobile notifications.
Get GitHub here and use it to record your Code Commits. Once you have a GitHub account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.

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

CoQ10 By Doctors Best Pre-Processing
CoQ10 By Doctors Best measurement values below 0 milligrams were assumed erroneous and removed. No maximum allowed measurement value was defined for CoQ10 By Doctors Best. It was assumed that any gaps in CoQ10 By Doctors Best data were unrecorded 0 milligrams measurement values.
CoQ10 By Doctors Best Analysis Settings

Code Commits Pre-Processing
Code Commits measurement values below 0 event were assumed erroneous and removed. No maximum allowed measurement value was defined for Code Commits. It was assumed that any gaps in Code Commits data were unrecorded 0 event measurement values.
Code Commits Analysis Settings

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in CoQ10 By Doctors Best would produce an observable change in Code Commits. It was assumed that CoQ10 By Doctors Best could produce an observable change in Code Commits for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
670 raw CoQ10 By Doctors Best measurements with 136 changes spanning 1223 days from 2015-07-18 to 2018-11-22 were used in this analysis. 87338 raw Code Commits measurements with 1633 changes spanning 2081 days from 2013-07-19 to 2019-03-31 were used in this analysis.

Data Sources

CoQ10 By Doctors Best 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.

Code Commits data was primarily collected using GitHub. GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over four million people use GitHub to build amazing things together.

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 weakly positive relationship between CoQ10 By Doctors Best intake and Code Commits

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. 1257 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their CoQ10 By Doctors Best intake 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 CoQ10 By Doctors Best intake and Code Commits 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 CoQ10 By Doctors Best intake
Effect Variable Name Code Commits
Sinn Predictive Coefficient 0.266
Confidence Level high
Confidence Interval 6.3617636540496
Forward Pearson Correlation Coefficient 0.266
Critical T Value 1.646
Total Co Q10 By Doctors Best intake Over Previous 7 days Before ABOVE Average Code Commits 550.32 milligrams
Total Co Q10 By Doctors Best intake Over Previous 7 days Before BELOW Average Code Commits 298.94 milligrams
Duration of Action 7 days
Effect Size weakly positive
Number of Paired Measurements 1257
Optimal Pearson Product 0.20583365792551
P Value 3.841650593355E-14
Statistical Significance 0.9999
Strength of Relationship 6.3617636540496
Study Type individual
Analysis Performed At 2019-04-04

CoQ10 By Doctors Best Statistics

Property Value
Variable Name CoQ10 By Doctors Best
Aggregation Method SUM
Analysis Performed At 2019-01-25
Duration of Action 7 days
Kurtosis 4.4216106272873
Mean 22.593 milligrams
Median 0 milligrams
Minimum Allowed Value 0 milligrams
Number of Changes 136
Number of Correlations 251
Number of Measurements 670
Onset Delay 30 minutes
Standard Deviation 43.457396760059
Unit Milligrams
UPC 753950003323
Variable ID 5627141
Variance 1888.5453331612

Code Commits Statistics

Property Value
Variable Name Code Commits
Aggregation Method SUM
Analysis Performed At 2019-03-31
Duration of Action 7 days
Kurtosis 101.83500926551
Mean 41.325 event
Median 15 event
Minimum Allowed Value 0 event
Number of Changes 1633
Number of Correlations 2584
Number of Measurements 87338
Onset Delay 0 seconds
Standard Deviation 93.522658821126
Unit Event
Variable ID 5955693
Variance 8746.4877129727

Tracking CoQ10 By Doctors Best

Record your CoQ10 By Doctors Best daily in the reminder inbox or using the interactive web or mobile notifications.

Tracking Code Commits

Get GitHub here and use it to record your Code Commits. Once you have a GitHub account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.
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https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn