5  How We Feel

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5.1 EDA

Figure 5.1: Most reported affective states reported using the How We Feel app.

Are they close to the middle

Figure 5.2: Most

5.2 Time of day

Figure 5.3: Time of day trends in arousal and valence.

5.3 Weather

(a) Valence

(b) Arousal

Figure 5.4: ?(caption)

             Df Sum Sq Mean Sq F value Pr(>F)  
weather       4   62.1  15.525    2.46 0.0456 *
Residuals   291 1836.8   6.312                 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
104 observations deleted due to missingness

    Pairwise comparisons using t tests with pooled SD 

data:  hwf$valence and hwf$weather 

       clear sky clouds rain  snow 
clouds 1.000     -      -     -    
rain   1.000     1.000  -     -    
snow   0.624     1.000  1.000 -    
other  0.093     0.149  0.637 1.000

P value adjustment method: bonferroni 

  Posthoc multiple comparisons of means: Scheffe Test 
    95% family-wise confidence level

$weather
                       diff    lwr.ci    upr.ci   pval    
clouds-clear sky -0.7434293 -2.699587 1.2127281 0.8460    
rain-clear sky   -0.5647059 -3.323802 2.1943901 0.9822    
snow-clear sky   -2.0147059 -5.354060 1.3246481 0.4795    
other-clear sky  -2.1456583 -4.686746 0.3954291 0.1471    
rain-clouds       0.1787234 -1.895485 2.2529316 0.9994    
snow-clouds      -1.2712766 -4.071458 1.5289045 0.7393    
other-clouds     -1.4022290 -3.176166 0.3717085 0.2018    
snow-rain        -1.4500000 -4.859849 1.9598494 0.7837    
other-rain       -1.5809524 -4.213995 1.0520902 0.4846    
other-snow       -0.1309524 -3.366936 3.1050309 1.0000    

---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

             Df Sum Sq Mean Sq F value Pr(>F)
weather       4   35.8   8.952   0.996   0.41
Residuals   291 2614.8   8.986               
104 observations deleted due to missingness

    Pairwise comparisons using t tests with pooled SD 

data:  hwf$arousal and hwf$weather 

       clear sky clouds rain snow
clouds 1         -      -    -   
rain   1         1      -    -   
snow   1         1      1    -   
other  1         1      1    1   

P value adjustment method: bonferroni 

  Posthoc multiple comparisons of means: Scheffe Test 
    95% family-wise confidence level

$weather
                        diff    lwr.ci   upr.ci   pval    
clouds-clear sky  1.21476846 -1.119199 3.548736 0.6267    
rain-clear sky    0.77647059 -2.515514 4.068455 0.9699    
snow-clear sky    2.05147059 -1.932842 6.035783 0.6365    
other-clear sky   0.70028011 -2.331590 3.732150 0.9721    
rain-clouds      -0.43829787 -2.913116 2.036520 0.9897    
snow-clouds       0.83670213 -2.504303 4.177707 0.9626    
other-clouds     -0.51448835 -2.631042 1.602065 0.9664    
snow-rain         1.27500000 -2.793424 5.343424 0.9179    
other-rain       -0.07619048 -3.217776 3.065395 1.0000    
other-snow       -1.35119048 -5.212168 2.509787 0.8816    

---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

5.4 Comparing valences from Daylio and HWF

Figure 5.5: Comparison of self-raported mood data using the Daylio app versus the How We Feel app.

(a) How We Feel

(b) Daylio

Figure 5.6: It doesn’t look like there’s a relationship between arousal and mood at the daily level.