# Temporal Variations Dataset for Indoor Environmental Parameters in Northern Saudi Arabia
## 4 Dataset Description
### Measures of Association  
The association is measured using correlation and covariance. The correlation is a measure of the linear relationship between two variables. The covariance measures how two variables change together, indicating the direction of the relationship between them. The data in Table 7 and Figure 5 represents the correlation matrix for the five measures you previously discussed: light, temperature, humidity, pressure, and attitude. Correlation values range from \(-1\) to \(1\), where \(-1\) indicates a perfect negative correlation, 1 indicates a perfect positive correlation, and 0 indicates no correlation. Here are the interpretations for each pair: \begin{table}
\begin{tabular}{c c c c c c} \hline
**Measure** & **Light** & **Temperature** & **Humidity** & **Pressure** & **Attitude** \\  & **(Lumen (Im))** & **(\({}^{\circ}\)C)** & **(\%)** & **(\%)** & **(Pascal (Pa))** & **0.144958** \\ \hline Skewness & 0.641172 & \(-1.223877\) & 3.668192 & \(-0.141923\) & 0.144958 \\ \hline Kurtosis & \(-1.270747\) & 2.977807 & 16.744838 & 0.190931 & 0.190579 \\ \hline \end{tabular}
\end{table} 
Table 6: Measures of shape. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Correlation** & **Light** & **Temperature** & **Humidity** & **Pressure** & **Attitude** \\  & **(Lumen (Im))** & **(\({}^{\circ}\)C)** & **(\%)** & **(\%)** & **(Pascal (Pa))** & **0.051339** \\ \hline Light & 1.000000 & \(-0.282322\) & 0.187878 & \(-0.051294\) & 0.051339 \\ \hline Temperature & \(-0.282322\) & 1.000000 & \(-0.395346\) & \(-0.195911\) & 0.195760 \\ \hline Humidity & 0.187878 & \(-0.395346\) & 1.000000 & \(-0.094870\) & 0.094785 \\ \hline Pressure & \(-0.051294\) & \(-0.195911\) & \(-0.094870\) & 1.000000 & \(-0.999907\) \\ \hline Attitude & 0.051339 & 0.195760 & 0.094785 & \(-0.999907\) & 1.000000 \\ \hline \end{tabular}
\end{table} 
Table 7: Measures of association. Light and Temperature: There's a negative correlation of \(-0.282322\), suggesting that as light levels increase, the temperature tends to decrease, and vice versa, although the relationship is not strong. Light and Humidity: The correlation is positive (0.187878) but weak, implying that light and humidity levels increase together to some extent. Light and Pressure: The correlation is weak and negative (\(-0.051294\)), suggesting a minimal tendency for light and pressure to move in opposite directions. Light and Attitude: The correlation is weak and positive (0.051339), implying a slight tendency for light and attitude to move in the same direction. Temperature and Humidity: There is a moderate negative correlation of \(-0.395346\), implying that as the temperature rises, humidity tends to fall, and vice versa. Temperature and Pressure: The correlation is negative (\(-0.195911\)), suggesting that temperature and pressure tend to move in opposite directions, but the relationship is not very strong. Temperature and Attitude: A weak positive correlation (0.195760) implies a slight tendency for temperature and attitude to move in the same direction. Humidity and Pressure: The correlation is weak and negative (\(-0.094870\)), suggesting a minimal tendency for humidity and pressure to move in opposite directions. Humidity and Attitude: The correlation is weak and positive (0.094785), suggesting a slight tendency for humidity and attitude to increase together. Pressure and Attitude: The correlation is strongly negative (\(-0.999907\)), indicating a very strong tendency for pressure and attitude to move in opposite directions. This correlation matrix can provide insights into the relationships between different pairs of variables. However, it is important to note that correlation does not imply causation, and these relationships might be influenced by other factors not included in the analysis. The covariance, which measures how much two random variables change together, is presented in Table 8. It is positive if the variables tend to show similar behavior, negative if they show opposite behavior, and zero if there is no relationship between their behavior.