# Temporal Variations Dataset for Indoor Environmental Parameters in Northern Saudi Arabia
## 4 Dataset Description
### Measures of Shape  
Skewness is defined as a measure of the symmetry or asymmetry of the distribution of the data, while Kurtosis means a measure of the \"tailedness\" of the distribution, indicating whether the data has heavy or light tails compared to a normal distribution.  
Table 6 provides two statistical measures--skewness and kurtosis--for five different parameters.  
Light: The skewness value of 0.641 indicates a moderate positive (right) skewness, meaning that the light distribution has a longer tail on the right. This suggests that there are periods with unusually high light intensities. The negative kurtosis of \(-1.27\) indicates a distribution flatter (\"platykurtic\") than the normal distribution. This suggests that light intensities are quite diverse and not clustered around the mean.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Measure** & **Light** & **Temperature** & **Humidity** & **Pressure** & **Attitude** \\  & **(Lumen (lm))** & **(\({}^{\circ}\)C)** & **(\%)** & **(\%)** & **(\%)** \\ \hline std & 305.715927 & 1.64157 & 1.827553 & 140.646670 & 12.951571 \\ \hline min & 0.000000 & 29.30000 & 10.000000 & 88,982.000000 & 999.590000 \\ \hline max & 856.000000 & 40.20000 & 25.000000 & 89,882.000000 & 1082.210000 \\ \hline Range & 856.00 & 10.90 & 15.00 & 900.00 & 82.62 \\ \hline Variance & 93,462.227717 & 2.694752 & 3.339950 & 19,781.485821 & 167.743187 \\ \hline IQR & 565.00 & 1.90 & 1.00 & 186.75 & 17.22 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Measure of dispersion.  
Temperature: The negative skewness of \(-1.22\) suggests a left-skewed distribution, meaning lower temperatures deviate from the average more than the higher ones. The kurtosis value of 2.98 indicates a distribution with heavier tails and a sharper peak (\"leptokurtic\") than the normal distribution. This suggests that there are more extreme temperature values (both high and low) than what would be expected in a normal distribution.  
Humidity: With a very high skewness value of 3.67, the humidity distribution is highly skewed to the right. This implies that there are periods with extraordinarily high humidity. A very high positive kurtosis value of 16.74 indicates that the distribution has heavy tails and a sharp peak, suggesting that extreme humidity values are more frequent than typical in a normal distribution.  
Pressure: The negative skewness value of \(-0.14\) suggests a slight left skew, though this value is relatively small, indicating the distribution is approximately symmetric. A positive kurtosis value of 0.19 suggests that the pressure distribution is slightly more peaked with heavier tails than the normal distribution.  
Attitude: A positive skewness of 0.14 indicates a slight right skewness, though this value is quite small, implying a nearly symmetric distribution. The kurtosis value of 0.19 indicates a slightly leptokurtic distribution, suggesting a sharper peak and heavier tails than the normal distribution.  
These values are indicative of the nature of data distribution. However, it would still be beneficial to visualize these distributions, for example, by using histograms or density plots. This would provide a clearer picture of the data distribution in each measure.