Hypothesis Testing using Bootstrap, Resampling, and Confidence Intervals

Entrega de la actividad 1

Time Series Component Analysis Decomposing the time series yields the following components: Trend: The trend component is an indication of the gradual increase in the sales of used cars over time, showing a long-term upward movement in the data. Seasonality: There is a distinct repeating seasonal pattern, suggesting that used car sales fluctuate consistently each year. Cyclic Component: There are no marked cyclic variations apart from the seasonal ones; therefore, economic cycles seem not to be a contributing factor in this data set. Residual: The residual component includes random fluctuations that cannot be described by either trend or seasonality and, therefore, represents unpredictable variations in sales data. However, from the Augmented Dickey-Fuller test result, this series is stationary since the p-value falls below the threshold 0.05 of 0.01, meaning there is evidence that this is not a series with a unit root; thus, no differencing would be required in order to apply some time series models.

min.pct = 0, logfc.threshold = 0

Final paper on association rules to pass Unsupervised Learning at the University of Warsaw

Este informe final detalla todo el proceso de análisis integral, las conclusiones y las recomendaciones estratégicas para la evaluación de la oferta inmobiliaria urbana.

the paper shows lifestyle patterns by using association rules