ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Tahitian Village

Bastrop, TX 78602
Resale homes · closed Nov 7 – Nov 6, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 7, 2026 · 7:22 AM CST
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
72
single-family resale homes
Median net sale price
$361,000
average $395,999
Median net price per SF
$200
average $205
Median days on market
89 days
average 122 days
1. SummaryResale homes · 72 sales · November 7, 2025 – November 6, 2026

This study looks at the 72 resale homes sold in Tahitian Village in the 365 days to November 6, 2026. A full year is used because only 39 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

Each comparison has its own section (3–6) with everything about it in one place: the key differences, a table of every measure at a glance, the charts and the numbers.

2. Where the resale homes sold72 resale homes · colored by price range

Each dot is one resale home, colored by its price range. Use the buttons to show one price range at a time. Click a dot for that sale: address, close date, original and last list price, net sale price, living area, net sale per SF and days on market. Scroll or pinch to zoom.

Under $304K · 18 sales$304K–$357K · 18 sales$365K–$439K · 17 salesOver $439K · 19 sales
3. Quartiles by net sale priceResale homes · 72 sales · November 7, 2025 – November 6, 2026

Sales ranked by net sale price and cut into four equal groups. This is the usual way to read a market by price.

2026-11-07T07:22:37.032657 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 18 18 17 19 72 sales Sales per group Under $304K: 18 sales (25%) $304K–$357K: 18 sales (25%) $365K–$439K: 17 sales (24%) Over $439K: 19 sales (26%)
Bottom line

3.1 Key differences

The top group against the bottom group. Only real differences are listed. Section 8 explains each measure.

Under $304K$304K–$357K$365K–$439KOver $439K
Higher-priced homes Over $439K
  • Are much larger.
Lower-priced homes Under $304K
  • Are much smaller.

3.2 At a glance

Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.

Under $304K$304K–$357K$365K–$439KOver $439KReal difference?
Net price per SF$188 per SF$193 per SF$209 per SF$229 per SFunclear
Living area1,515 SFSmallest1,723 SF1,899 SF2,618 SFLargest✓ large
Year built2006201020202013unclear
Days on market94 days70 days80 days125 daysunclear
Discount from original list10.5%5.8%7.2%9.3%unclear
Price cut before sale78%56%65%84%unclear
Seller paid closing costs or repairs44%94%53%58%unclear
Has a view50%50%76%84%unclear

How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.

3.3 Net price per SF: no clear difference

2026-11-07T07:22:37.064457 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $304K 18 sales $304K– $357K 18 sales $365K– $439K 17 sales Over $439K 19 sales $0 $100 $200 $188 $193 $209 $229 Net price per SF, average

The average is $229 per SF for homes over $439K and $188 per SF for homes under $304K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $439K are about 1,100 SF (73%) larger than homes under $304K

2026-11-07T07:22:37.087125 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $304K 18 sales $304K– $357K 18 sales $365K– $439K 17 sales Over $439K 19 sales 0 1,000 2,000 3,000 1,515 1,723 1,899 2,618 Living area (SF), average

The average is 2,618 SF for homes over $439K and 1,515 SF for homes under $304K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-11-07T07:22:37.113139 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $304K 18 sales $304K– $357K 18 sales $365K– $439K 17 sales Over $439K 19 sales 1998 2004 2010 2016 2022 2006 2010 2020 2013 Year built: median (dot) and middle half (bar)

The median is 2013 for homes over $439K and 2006 for homes under $304K. It does not move in a straight line; homes $365K–$439K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-07T07:22:37.138248 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $304K 18 sales $304K– $357K 18 sales $365K– $439K 17 sales Over $439K 19 sales 0 50 100 150 94 70 80 125 Days on market, median

The median is 125 days for homes over $439K and 94 days for homes under $304K. It does not move in a straight line; homes over $439K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-07T07:22:37.160917 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $304K 18 sales $304K– $357K 18 sales $365K– $439K 17 sales Over $439K 19 sales 0.0% 5.0% 10.0% 10.5% 5.8% 7.2% 9.3% Discount from original list, average

The average is 9.3% for homes over $439K and 10.5% for homes under $304K. It does not move in a straight line; homes under $304K are highest. Defined in 8.1.6.

– No clear difference · could be chance

3.8 How often: price cut before sale, seller paid closing costs or repairs, has a view

2026-11-07T07:22:37.192687 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 78 44 50 56 94 50 65 53 76 84 58 84 Under $304K $304K–$357K $365K–$439K Over $439K

Each bar is the share of homes in the group, in percent.

  • 84% of homes over $439K had a price cut before sale, against 78% of homes under $304K. Defined in 8.1.7.
  • 58% of homes over $439K had the seller pay closing costs or repairs, against 44% of homes under $304K. Defined in 8.1.8.
  • 84% of homes over $439K have a view, against 50% of homes under $304K. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

3.9 The numbers: price and size

Under $304K18 sales$304K–$357K18 sales$365K–$439K17 salesOver $439K19 salesAll72 salesReal difference?
Net sale price average$278,055$328,278$395,559$572,285$395,999by design
Net price per SF average$188$193$209$229$205unclear
Living area average1,5151,7231,8992,6181,949✓ large
Year built median20062010202020132014unclear

3.10 The numbers: selling

Under $304K18 sales$304K–$357K18 sales$365K–$439K17 salesOver $439K19 salesAll72 salesReal difference?
Days on market median94708012589unclear
Discount from original list average10.5%5.8%7.2%9.3%8.2%unclear
Price cut before sale78%56%65%84%71%unclear
Seller paid closing costs or repairs44%94%53%58%62%unclear
Has a view50%50%76%84%65%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.1.

4. Quartiles by living areaResale homes · 72 sales · November 7, 2025 – November 6, 2026

Sales ranked by living area and cut into four equal groups, from the smallest homes to the largest.

2026-11-07T07:22:37.215585 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 18 18 18 18 72 sales Sales per group Under 1,591 SF: 18 sales (25%) 1,591–1,817 SF: 18 sales (25%) 1,824–2,055 SF: 18 sales (25%) Over 2,055 SF: 18 sales (25%)
Bottom line

4.1 Key differences

The top group against the bottom group. Only real differences are listed. Section 8 explains each measure.

Under 1,591 SF1,591–1,817 SF1,824–2,055 SFOver 2,055 SF
Larger homes Over 2,055 SF
  • Sell for much more.
Smaller homes Under 1,591 SF
  • Sell for much less.

4.2 At a glance

Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.

Under 1,591 SF1,591–1,817 SF1,824–2,055 SFOver 2,055 SFReal difference?
Net sale price$293KLowest$351K$390K$549KHighest✓ large
Net price per SF$213 per SF$208 per SF$202 per SF$198 per SFunclear
Year built2008200920202009unclear
Days on market82 days116 days56 days124 daysunclear
Discount from original list8.0%7.9%6.3%10.7%unclear
Price cut before sale72%72%56%83%unclear
Seller paid closing costs or repairs67%56%61%67%unclear
Has a view33%67%78%83%unclear

4.3 Homes over 2,055 SF sell for about $256K (87%) more than homes under 1,591 SF

2026-11-07T07:22:37.236561 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,591 SF 18 sales 1,591– 1,817 SF 18 sales 1,824– 2,055 SF 18 sales Over 2,055 SF 18 sales $0K $200K $400K $600K $293K $351K $390K $549K Net sale price, average

The average is $549K for homes over 2,055 SF and $293K for homes under 1,591 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-11-07T07:22:37.260513 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,591 SF 18 sales 1,591– 1,817 SF 18 sales 1,824– 2,055 SF 18 sales Over 2,055 SF 18 sales $0 $100 $200 $213 $208 $202 $198 Net price per SF, average

The average is $198 per SF for homes over 2,055 SF and $213 per SF for homes under 1,591 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-07T07:22:37.284361 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,591 SF 18 sales 1,591– 1,817 SF 18 sales 1,824– 2,055 SF 18 sales Over 2,055 SF 18 sales 2005 2010 2015 2020 2008 2009 2020 2009 Year built: median (dot) and middle half (bar)

The median is 2009 for homes over 2,055 SF and 2008 for homes under 1,591 SF. It does not move in a straight line; homes 1,824–2,055 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-07T07:22:37.308142 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,591 SF 18 sales 1,591– 1,817 SF 18 sales 1,824– 2,055 SF 18 sales Over 2,055 SF 18 sales 0 50 100 82 116 56 124 Days on market, median

The median is 124 days for homes over 2,055 SF and 82 days for homes under 1,591 SF. It does not move in a straight line; homes over 2,055 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-07T07:22:37.330314 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,591 SF 18 sales 1,591– 1,817 SF 18 sales 1,824– 2,055 SF 18 sales Over 2,055 SF 18 sales 0.0% 5.0% 10.0% 8.0% 7.9% 6.3% 10.7% Discount from original list, average

The average is 10.7% for homes over 2,055 SF and 8.0% for homes under 1,591 SF. It does not move in a straight line; homes over 2,055 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

4.8 How often: price cut before sale, seller paid closing costs or repairs, has a view

2026-11-07T07:22:37.357712 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 72 67 33 72 56 67 56 61 78 83 67 83 Under 1,591 SF 1,591–1,817 SF 1,824–2,055 SF Over 2,055 SF

Each bar is the share of homes in the group, in percent.

  • 83% of homes over 2,055 SF had a price cut before sale, against 72% of homes under 1,591 SF. Defined in 8.1.7.
  • 67% of homes over 2,055 SF had the seller pay closing costs or repairs, against 67% of homes under 1,591 SF. Defined in 8.1.8.
  • 83% of homes over 2,055 SF have a view, against 33% of homes under 1,591 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 1,591 SF18 sales1,591–1,817 SF18 sales1,824–2,055 SF18 salesOver 2,055 SF18 salesAll72 salesReal difference?
Net sale price average$293,062$351,251$390,413$549,269$395,999✓ large
Net price per SF average$213$208$202$198$205unclear
Living area average1,3921,6961,9352,7721,949by design
Year built median20082009202020092014unclear

4.10 The numbers: selling

Under 1,591 SF18 sales1,591–1,817 SF18 sales1,824–2,055 SF18 salesOver 2,055 SF18 salesAll72 salesReal difference?
Days on market median821165612489unclear
Discount from original list average8.0%7.9%6.3%10.7%8.2%unclear
Price cut before sale72%72%56%83%71%unclear
Seller paid closing costs or repairs67%56%61%67%62%unclear
Has a view33%67%78%83%65%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.2.

5. Quartiles by year builtResale homes · 72 sales · November 7, 2025 – November 6, 2026

Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little.

2026-11-07T07:22:37.380240 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 17 19 19 17 72 sales Sales per group Before 2003: 17 sales (24%) 2003–2013: 19 sales (26%) 2014–2020: 19 sales (26%) After 2020: 17 sales (24%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

The top group against the bottom group: no measure differs enough to rule out chance.

5.2 At a glance

Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.

Before 20032003–20132014–2020After 2020Real difference?
Net sale price$378K$398K$393K$416Kunclear
Net price per SF$201 per SF$192 per SF$229 per SF$197 per SFunclear
Living area1,871 SF2,039 SF1,744 SF2,153 SFunclear
Days on market76 days89 days100 days79 daysunclear
Discount from original list8.5%10.6%6.3%7.5%unclear
Price cut before sale76%89%58%59%unclear
Seller paid closing costs or repairs59%63%58%71%unclear
Has a view71%63%74%53%unclear

5.3 Net sale price: no clear difference

2026-11-07T07:22:37.402594 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2013 19 sales 2014– 2020 19 sales After 2020 17 sales $0K $200K $400K $378K $398K $393K $416K Net sale price, average

The average is $416K for homes built after 2020 and $378K for homes built before 2003. It does not move in a straight line; homes built after 2020 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-07T07:22:37.428011 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2013 19 sales 2014– 2020 19 sales After 2020 17 sales $0 $100 $200 $201 $192 $229 $197 Net price per SF, average

The average is $197 per SF for homes built after 2020 and $201 per SF for homes built before 2003. It does not move in a straight line; homes built 2014–2020 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-07T07:22:37.451190 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2013 19 sales 2014– 2020 19 sales After 2020 17 sales 0 1,000 2,000 1,871 2,039 1,744 2,153 Living area (SF), average

The average is 2,153 SF for homes built after 2020 and 1,871 SF for homes built before 2003. It does not move in a straight line; homes built after 2020 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-07T07:22:37.474946 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2013 19 sales 2014– 2020 19 sales After 2020 17 sales 0 50 100 76 89 100 79 Days on market, median

The median is 79 days for homes built after 2020 and 76 days for homes built before 2003. It does not move in a straight line; homes built 2014–2020 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-07T07:22:37.500149 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2013 19 sales 2014– 2020 19 sales After 2020 17 sales 0.0% 5.0% 10.0% 8.5% 10.6% 6.3% 7.5% Discount from original list, average

The average is 7.5% for homes built after 2020 and 8.5% for homes built before 2003. It does not move in a straight line; homes built 2003–2013 are highest. Defined in 8.1.6.

– No clear difference · could be chance

5.8 How often: price cut before sale, seller paid closing costs or repairs, has a view

2026-11-07T07:22:37.531848 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 76 59 71 89 63 63 58 58 74 59 71 53 Before 2003 2003–2013 2014–2020 After 2020

Each bar is the share of homes in the group, in percent.

  • 59% of homes built after 2020 had a price cut before sale, against 76% of homes built before 2003. Defined in 8.1.7.
  • 71% of homes built after 2020 had the seller pay closing costs or repairs, against 59% of homes built before 2003. Defined in 8.1.8.
  • 53% of homes built after 2020 have a view, against 71% of homes built before 2003. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

5.9 The numbers: price and size

Before 200317 sales2003–201319 sales2014–202019 salesAfter 202017 salesAll72 salesReal difference?
Net sale price average$377,859$397,740$392,855$415,706$395,999unclear
Net price per SF average$201$192$229$197$205unclear
Living area average1,8712,0391,7442,1531,949unclear
Year built median19962007201720222014by design

5.10 The numbers: selling

Before 200317 sales2003–201319 sales2014–202019 salesAfter 202017 salesAll72 salesReal difference?
Days on market median76891007989unclear
Discount from original list average8.5%10.6%6.3%7.5%8.2%unclear
Price cut before sale76%89%58%59%71%unclear
Seller paid closing costs or repairs59%63%58%71%62%unclear
Has a view71%63%74%53%65%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.3.

6. View and no viewResale homes · 72 sales · November 7, 2025 – November 6, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-07T07:22:37.554080 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 47 24 71 sales Sales per group View: 47 sales (66%) No view: 24 sales (34%)
Bottom line

6.1 Key differences

The top group against the bottom group. Only real differences are listed. Section 8 explains each measure.

ViewNo view
Homes with a view MLS lists a view
  • Are larger.
  • Sell for more.
Homes without a view no view listed
  • Are smaller.
  • Sell for less.

6.2 At a glance

Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.

ViewNo viewReal difference?
Net sale price$425KHighest$343KLowest✓ medium
Net price per SF$205 per SF$204 per SFunclear
Living area2,092 SFLargest1,692 SFSmallest✓ medium
Year built20132017unclear
Days on market85 days96 daysunclear
Discount from original list8.5%7.8%unclear
Price cut before sale66%79%unclear
Seller paid closing costs or repairs62%62%unclear

6.3 Homes with a view sell for about $82K (24%) more than homes without a view

2026-11-07T07:22:37.572989 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 47 sales No view 24 sales $0K $200K $400K $425K $343K Net sale price, average

The average is $425K for homes with a view and $343K for homes without a view. Defined in 8.1.1.

✓ Real difference · medium

6.4 Net price per SF: no clear difference

2026-11-07T07:22:37.593563 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 47 sales No view 24 sales $0 $50 $100 $150 $200 $205 $204 Net price per SF, average

The average is $205 per SF for homes with a view and $204 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Homes with a view are about 400 SF (24%) larger than homes without a view

2026-11-07T07:22:37.701788 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 47 sales No view 24 sales 0 1,000 2,000 2,092 1,692 Living area (SF), average

The average is 2,092 SF for homes with a view and 1,692 SF for homes without a view. Defined in 8.1.3.

✓ Real difference · medium

6.6 Year built: no clear difference

2026-11-07T07:22:37.722571 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 47 sales No view 24 sales 2005 2010 2015 2020 2013 2017 Year built: median (dot) and middle half (bar)

The median is 2013 for homes with a view and 2017 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-07T07:22:37.743623 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 47 sales No view 24 sales 0 25 50 75 100 85 96 Days on market, median

The median is 85 days for homes with a view and 96 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-11-07T07:22:37.762918 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 47 sales No view 24 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.5% 7.8% Discount from original list, average

The average is 8.5% for homes with a view and 7.8% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

6.9 How often: price cut before sale, seller paid closing costs or repairs

2026-11-07T07:22:37.782701 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 66 62 79 62 View No view

Each bar is the share of homes in the group, in percent.

  • 66% of homes with a view had a price cut before sale, against 79% of homes without a view. Defined in 8.1.7.
  • 62% of homes with a view had the seller pay closing costs or repairs, against 62% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View47 salesNo view24 salesAll71 salesReal difference?
Net sale price average$425,067$342,660$397,211✓ medium
Net price per SF average$205$204$205unclear
Living area average2,0921,6921,957✓ medium
Year built median201320172014unclear

6.11 The numbers: selling

View47 salesNo view24 salesAll71 salesReal difference?
Days on market median859689unclear
Discount from original list average8.5%7.8%8.3%unclear
Price cut before sale66%79%70%unclear
Seller paid closing costs or repairs62%62%62%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 70 sales · November 7, 2025 – November 6, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 70 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in Tahitian Village.
MeasureAverageMedian
Sales70
Net sale price$385,375$375,000
Net price per SF$199$200
Living area (SF)1,9481,906
Days on market129108
Discount from original list6.3%4.9%
Price cut before sale57% of sales
Seller paid closing costs or repairs73% of sales
Year built2024–2026

Same definitions as the rest of the study (section 8). New construction = NewConstructionYN true, or PropertyCondition “New Construction” or “Under Construction”.

8. AppendixMeasures, methods and tests

Each measure and method three ways: in plain words, as statistics, and with the data from this study.

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
72 resale sales. Average $395,999; median $361,000; standard deviation $132,346; middle half (25th–75th percentile) $304,171–$440,000; lowest $248,000, highest $920,000. 45 sales had a seller payment; their median payment was $8,175.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
72 resale sales. Average $205; median $200; standard deviation $39; middle half (25th–75th percentile) $183–$219; lowest $118, highest $371.

8.1.3 Living area

In simple terms
The heated and cooled space, as listed in the MLS. Garages and porches are not counted.
Statistically
RESO LivingArea, in square feet. Sales under 400 SF are treated as entry errors and left out.
The data
72 resale sales. Average 1,949; median 1,820; standard deviation 601; middle half (25th–75th percentile) 1,578–2,056; lowest 1,233, highest 4,050.

8.1.4 Year built

In simple terms
The year the home was finished, as listed in the MLS. It shows whether a group leans to older or newer phases of the community.
Statistically
RESO YearBuilt; summarized by the median, with the 25th–75th percentile (middle half) on the charts.
The data
72 resale sales. Average 2010; median 2014; standard deviation 11; middle half (25th–75th percentile) 2003–2020; lowest 1978, highest 2025.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
72 resale sales. Average 122; median 89; standard deviation 120; middle half (25th–75th percentile) 49–165; lowest 2, highest 657. 0 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
72 resale sales. Average 8.2%; median 7.5%; standard deviation 5.9%; middle half (25th–75th percentile) 4.5%–10.5%; lowest 0.0%, highest 29.1%. 0 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
51 of 72 resale sales (70.8%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
45 of 72 resale sales (62.5%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
47 sales with a view, 24 without, 1 unclassified. Most common View entries: Trees/Woods 38, Neighborhood 27, None 13, Panoramic 10, Park/Greenbelt 6, Pool 5, Golf Course 5, Rural 5.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-07 13:15 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Bastrop, SubdivisionName contains any of “tahitian village” (case-insensitive). A record is kept when its subdivision name belongs to the Tahitian Village family, the same rule comparable sales use.
The data
Pulled November 7, 2026: 144 closed Tahitian Village records over the prior year, in ZIP 78602. 14 subdivision spellings kept, the most common: Tahitian Village, (88); Tahitian Village (37); Tahitian Village Unit 5 (4); Tahitian Village, Unit 5 (3); Tahitian Village Unit 04 (2); Tahitian Village Unit 03 (2); Tahitian Village Unit 05 (1); Tahitian Village Unit 1 (1); Tahitian Village Unit 4 (1); Tahitian Village, Unit 1 (1); Tahitian Village, Unit 4 (1); Tahitian Village Unit 02 (1); and 2 more (2 records). Names found by the search but not part of Tahitian Village, left out: Tahitian Villages (1); S7980 - Tahitian Village, Unit 1 (1).

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 39 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 7, 2025 to November 6, 2026 inclusive.
The data
142 single-family sales in the window: 72 resale, 70 new construction.

8.2.3 Resale and new construction

In simple terms
A resale home was previously owned. New construction is sold by the builder and behaves differently, so it is kept out of every analysis and reported once on its own.
Statistically
New construction = NewConstructionYN true, or PropertyCondition contains “New Construction” or “Under Construction”. Everything else is resale.
The data
72 resale; 70 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
2 sale(s) with concessions above 10% of price

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $304K”.
Statistically
Sort by the slicing variable; cut k sits at round(nk/4), k = 1…3. A cut that would split tied values moves to the nearer edge of the tie. A group under 3 sales merges into its smaller neighbor. Range names use the next group's lowest value (“Under”) and the previous group's highest value (“Over”/“After”).
The data
Quartiles by net sale price: Under $304K: $248,000–$304,000 (18 sales); $304K–$357K: $304,228–$357,000 (18 sales); $365K–$439K: $365,000–$439,000 (17 sales); Over $439K: $440,000–$920,000 (19 sales)
Quartiles by living area: Under 1,591 SF: 1,233–1,540 SF (18 sales); 1,591–1,817 SF: 1,591–1,817 SF (18 sales); 1,824–2,055 SF: 1,824–2,055 SF (18 sales); Over 2,055 SF: 2,060–4,050 SF (18 sales)
Quartiles by year built: Before 2003: 1978–2002 (17 sales); 2003–2013: 2003–2013 (19 sales); 2014–2020: 2014–2020 (19 sales); After 2020: 2021–2025 (17 sales)
View and no view: View: MLS lists a view (47 sales); No view: None or Neighborhood (24 sales)

8.2.6 Average and median

In simple terms
The average adds the values and divides by how many; one very expensive home can pull it up. The median is the middle value, with half above and half below.
Statistically
Mean x̄ = (1/n) Σ xᵢ; median = 50th percentile. Price, price per SF, living area and discount use the mean; days on market and year built use the median (skewed or whole-year values).
The data
Net sale price: average $395,999, median $361,000. Days on market: average 122, median 89: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.

8.2.8 Mann–Whitney U test

In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.

8.2.9 Chi-square test

In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
4 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.

8.3 Test results

Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 10.8430.0126p < 0.0063Unclearε² = 0.153large
Living areaKruskal–WallisH = 36.153< 0.0001p < 0.0063Yesε² = 0.509large
Year builtKruskal–WallisH = 12.2630.0066p < 0.0063Unclearε² = 0.173large
Days on marketKruskal–WallisH = 5.6030.1329p < 0.0063Unclearε² = 0.079medium
Discount from original listKruskal–WallisH = 5.6030.1327p < 0.0063Unclearε² = 0.079medium
Price cut before saleChi-squareχ² = 4.4130.2206p < 0.0063UnclearCramér’s V = 0.247small
Seller paid closing costs or repairsChi-squareχ² = 11.1830.0108p < 0.0063UnclearCramér’s V = 0.394medium
Has a viewChi-squareχ² = 7.6530.0538p < 0.0063UnclearCramér’s V = 0.326medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 42.693< 0.0001p < 0.0063Yesε² = 0.601large
Net price per SFKruskal–WallisH = 1.2330.7457p < 0.0063Unclearε² = 0.017small
Year builtKruskal–WallisH = 9.7630.0207p < 0.0063Unclearε² = 0.138medium
Days on marketKruskal–WallisH = 6.6830.0830p < 0.0063Unclearε² = 0.094medium
Discount from original listKruskal–WallisH = 5.1830.1589p < 0.0063Unclearε² = 0.073medium
Price cut before saleChi-squareχ² = 3.4330.3301p < 0.0063UnclearCramér’s V = 0.218small
Seller paid closing costs or repairsChi-squareχ² = 0.6530.8845p < 0.0063UnclearCramér’s V = 0.095negligible
Has a viewChi-squareχ² = 11.9530.0076p < 0.0063UnclearCramér’s V = 0.407medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.8330.1847p < 0.0063Unclearε² = 0.068medium
Net price per SFKruskal–WallisH = 6.7230.0816p < 0.0063Unclearε² = 0.095medium
Living areaKruskal–WallisH = 4.3030.2308p < 0.0063Unclearε² = 0.061medium
Days on marketKruskal–WallisH = 0.2330.9723p < 0.0063Unclearε² = 0.003negligible
Discount from original listKruskal–WallisH = 5.1930.1587p < 0.0063Unclearε² = 0.073medium
Price cut before saleChi-squareχ² = 6.1830.1030p < 0.0063UnclearCramér’s V = 0.293small
Seller paid closing costs or repairsChi-squareχ² = 0.7530.8619p < 0.0063UnclearCramér’s V = 0.102small
Has a viewChi-squareχ² = 1.9830.5759p < 0.0063UnclearCramér’s V = 0.166small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 792.50—0.0056p < 0.0063Yesrank-biserial r = 0.405medium
Net price per SFMann–Whitney UU = 595.00—0.7108p < 0.0063Unclearrank-biserial r = 0.055negligible
Living areaMann–Whitney UU = 814.00—0.0024p < 0.0063Yesrank-biserial r = 0.443medium
Year builtMann–Whitney UU = 473.00—0.2707p < 0.0063Unclearrank-biserial r = 0.161small
Days on marketMann–Whitney UU = 554.50—0.9129p < 0.0063Unclearrank-biserial r = 0.017negligible
Discount from original listMann–Whitney UU = 616.00—0.5313p < 0.0063Unclearrank-biserial r = 0.092negligible
Price cut before saleChi-squareχ² = 1.3310.2487p < 0.0063UnclearCramér’s V = 0.137small
Seller paid closing costs or repairsChi-squareχ² = 0.0010.9478p < 0.0063UnclearCramér’s V = 0.008negligible

8.4 Data notes

Left out of the analysis: 70 new-construction sales (basic statistics only, section 7); 2 sale(s) with concessions above 10% of price. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
  2. Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
  3. Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
  4. Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
  5. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
  6. Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
  7. Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
  8. Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 72 closed MLS resale sales; the 70 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 7, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.