class: center, middle, inverse, title-slide .title[ # Sample presentation ] .author[ ### Mike Wheeler, Eleven, Dustin Henderson, Lucas Sinclair, Will Byers ] .institute[ ### NTU ] .date[ ### 2022/11/07 (updated: 2025-07-14) ] --- # Motivation ## Problem statement We will construct a predictive model for the price of an HDB block to help owners to identify a right moment to sell. <img src="fig_hdb.jpg" width="60%"> --- ## Data sample We will work with the dataset `hdb_sales.csv` - resale transactions of HDB units between Jan 2017 and Jun 2020 downloaded on 4 Aug 2020 from * https://data.gov.sg/dataset/resale-flat-prices
--- ## One glance at the data Generally, large units cost more than small units: <img src="mh_4510_presentation_r_ninja_files/figure-html/unnamed-chunk-2-1.png" width="100%" height="60%" style="display: block; margin: auto;" /> --- # Modelling Our model is $$ \mbox{resale price} = \beta_0+\beta_1\times\mbox{remaining lease} + \beta_2\times\mbox{floor area} $$ Here is the table of coefficients <table style="text-align:center"><caption><strong>Regression model</strong></caption> <tr><td colspan="2" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left"></td><td><em>Dependent variable:</em></td></tr> <tr><td></td><td colspan="1" style="border-bottom: 1px solid black"></td></tr> <tr><td style="text-align:left"></td><td>resale_price</td></tr> <tr><td colspan="2" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">floor_area_sqm</td><td>3,738.1<sup>***</sup> (17.8)</td></tr> <tr><td style="text-align:left">remaining_lease</td><td>2,541.4<sup>***</sup> (34.1)</td></tr> <tr><td style="text-align:left">Constant</td><td>-116,482.7<sup>***</sup> (2,811.2)</td></tr> <tr><td colspan="2" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Observations</td><td>73,320</td></tr> <tr><td style="text-align:left">Adjusted R<sup>2</sup></td><td>0.4</td></tr> <tr><td colspan="2" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left"><em>Note:</em></td><td style="text-align:right"><sup>*</sup>p<0.1; <sup>**</sup>p<0.05; <sup>***</sup>p<0.01</td></tr> </table> --- # Analysis Model's residual depending on the town. The most popular location is Bukit Timah (highest median price when controlled for unit area and remaining lease): <img src="mh_4510_presentation_r_ninja_files/figure-html/unnamed-chunk-4-1.png" width="100%" height="60%" style="display: block; margin: auto;" /> --- Box plots by unit type
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