This individual's General Entertainment Activities is generally highest after an average of 1500 kilocalories of Calories Burned over the previous 7 days.
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Blue represents the mean of Calories Burned over the previous 7 days
An increase in 7 days cumulative Calories Burned is usually followed by an decrease in General Entertainment Activities. (R = -0.015)
Typical values for General Entertainment Activities following a given amount of Calories Burned over the previous 7 days.
Typical Calories Burned seen over the previous 7 days preceding the given General Entertainment Activities value.
Correlation between outcome and aggregated predictor measurements over given number of days
Peak correlation suggests the delay between predictor and observable outcome
This chart shows how Calories Burned changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Calories Burned on each day of the week.
This chart shows the typical value recorded for Calories Burned for each month of the year.
This chart shows how General Entertainment Activities changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for General Entertainment Activities on each day of the week.
This chart shows the typical value recorded for General Entertainment Activities for each month of the year.

Abstract

This individual's General Entertainment Activities is generally 14% higher than normal after an average of 1475 kilocalories Calories Burned over the previous 7 days. This individual's data suggests with a medium degree of confidence (p=0.37838081523169, 95% CI -0.036 to 0.006) that Calories Burned has a very weakly negative predictive relationship (R=-0.02) with General Entertainment Activities. The highest quartile of General Entertainment Activities measurements were observed following an average 2 kilocalories Calories Burned. The lowest quartile of General Entertainment Activities measurements were observed following an average 2364.0168981481 kcal Calories Burned. General Entertainment Activities is generally 12% lower than normal after an average of 2364.0168981481 kilocalories of Calories Burned over the previous 7 days. General Entertainment Activities is generally 14% higher after an average of 2 kilocalories of Calories Burned over the previous 7 days.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Calories Burned and General Entertainment Activities. Additionally, we attempt to determine the Calories Burned values most likely to produce optimal General Entertainment Activities values.

Participant Instructions

Get Fitbit here and use it to record your Calories Burned. Once you have a Fitbit account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.
Get RescueTime here and use it to record your General Entertainment Activities. Once you have a RescueTime 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

Calories Burned Pre-Processing
No minimum allowed measurement value was defined for Calories Burned. No maximum allowed measurement value was defined for Calories Burned. No missing data filling value was defined for Calories Burned so any gaps in data were just not analyzed instead of assuming zero values for those times.
Calories Burned Analysis Settings

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

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

Data Quantity
257 raw Calories Burned measurements with 220 changes spanning 260 days from 2018-10-26 to 2019-07-12 were used in this analysis. 1195 raw General Entertainment Activities measurements with 1433 changes spanning 2163 days from 2013-08-10 to 2019-07-13 were used in this analysis.

Data Sources

Calories Burned data was primarily collected using Fitbit. Fitbit makes activity tracking easy and automatic.

General Entertainment Activities data was primarily collected using RescueTime. Detailed reports show which applications and websites you spent time on. Activities are automatically grouped into pre-defined categories with built-in productivity scores covering thousands of websites and applications. You can customize categories and productivity scores to meet your needs.

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 Calories Burned and General Entertainment Activities

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. 223 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Calories Burned 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 Calories Burned and General Entertainment Activities 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 Calories Burned
Effect Variable Name General Entertainment Activities
Sinn Predictive Coefficient 0.0075
Confidence Level medium
Confidence Interval 0.021021639548265
Forward Pearson Predictive Coefficient -0.015
Critical T Value 1.646
Average Calories Burned Over Previous 7 days Before ABOVE Average General Entertainment Activities 2 kilocalories
Average Calories Burned Over Previous 7 days Before BELOW Average General Entertainment Activities 2 kilocalories
Duration of Action 7 days
Effect Size very weakly negative
Number of Paired Measurements 224
Optimal Pearson Product -0.0012376422001892
P Value 0.37838081523169
Statistical Significance 0.9984
Strength of Relationship 0.021021639548265
Study Type individual
Analysis Performed At 2019-07-14

Calories Burned Statistics

Property Value
Variable Name Calories Burned
Aggregation Method MEAN
Analysis Performed At 2019-07-13
Duration of Action 7 days
Kurtosis 3.2738743705691
Mean 2365.6 kilocalories
Median 2350 kilocalories
Number of Changes 220
Number of Correlations 3209
Number of Measurements 257
Onset Delay 0 seconds
Standard Deviation 616.1775072347
Unit Kilocalories
Variable ID 1280
Variance 379674.72042197

General Entertainment Activities Statistics

Property Value
Variable Name General Entertainment Activities
Aggregation Method SUM
Analysis Performed At 2019-07-14
Duration of Action 7 days
Kurtosis 82.128199774057
Maximum Allowed Value 7 days
Mean 7 minutes
Median 6 seconds
Minimum Allowed Value 0 seconds
Number of Changes 1433
Number of Correlations 101
Number of Measurements 1195
Onset Delay 0 seconds
Standard Deviation 0.40668413163828
Unit Hours
UPC 885289372679
Variable ID 5956888
Variance 0.16539198292638

Tracking Calories Burned

Get Fitbit here and use it to record your Calories Burned. Once you have a Fitbit account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.

Tracking General Entertainment Activities

Get RescueTime here and use it to record your General Entertainment Activities. Once you have a RescueTime 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