ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Tahitian Village,

Bastrop, TX 78602
Resale homes · closed Nov 3 – Nov 2, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 3, 2026 · 7:12 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
69
single-family resale homes
Median net sale price
$365,000
average $398,542
Median net price per SF
$202
average $206
Median days on market
89 days
average 124 days
1. SummaryResale homes · 69 sales · November 3, 2025 – November 2, 2026

This study looks at the 69 resale homes sold in Tahitian Village, in the 365 days to November 2, 2026. A full year is used because only 37 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 sold69 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 $309K · 17 sales$309K–$357K · 17 sales$365K–$439K · 17 salesOver $439K · 18 sales
3. Quartiles by net sale priceResale homes · 69 sales · November 3, 2025 – November 2, 2026

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

2026-11-03T07:12:44.666550 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 17 17 17 18 69 sales Sales per group Under $309K: 17 sales (25%) $309K–$357K: 17 sales (25%) $365K–$439K: 17 sales (25%) Over $439K: 18 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 $309K$309K–$357K$365K–$439KOver $439K
Higher-priced homes Over $439K
  • Are much larger.
Lower-priced homes Under $309K
  • 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 $309K$309K–$357K$365K–$439KOver $439KReal difference?
Net price per SF$191 per SF$192 per SF$209 per SF$231 per SFunclear
Living area1,495 SFSmallest1,740 SF1,899 SF2,632 SFLargest✓ large
Year built2004200920202014unclear
Days on market100 days69 days80 days140 daysunclear
Discount from original list10.3%5.8%7.2%9.7%unclear
Price cut before sale82%53%65%83%unclear
Seller paid closing costs or repairs53%94%53%61%unclear
Has a view41%53%76%83%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

2026-11-03T07:12:44.695177 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $309K 17 sales $309K– $357K 17 sales $365K– $439K 17 sales Over $439K 18 sales $0 $100 $200 $191 $192 $209 $231 Net price per SF, average

The average is $231 per SF for homes over $439K and $191 per SF for homes under $309K. 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 1,140 SF (76%) larger than homes under $309K

2026-11-03T07:12:44.717691 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $309K 17 sales $309K– $357K 17 sales $365K– $439K 17 sales Over $439K 18 sales 0 1,000 2,000 3,000 1,495 1,740 1,899 2,632 Living area (SF), average

The average is 2,632 SF for homes over $439K and 1,495 SF for homes under $309K. 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

2026-11-03T07:12:44.742921 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $309K 17 sales $309K– $357K 17 sales $365K– $439K 17 sales Over $439K 18 sales 1998 2004 2010 2016 2022 2004 2009 2020 2014 Year built: median (dot) and middle half (bar)

The median is 2014 for homes over $439K and 2004 for homes under $309K. 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

2026-11-03T07:12:44.766231 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $309K 17 sales $309K– $357K 17 sales $365K– $439K 17 sales Over $439K 18 sales 0 50 100 150 100 69 80 140 Days on market, median

The median is 140 days for homes over $439K and 100 days for homes under $309K. 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

2026-11-03T07:12:44.788248 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $309K 17 sales $309K– $357K 17 sales $365K– $439K 17 sales Over $439K 18 sales 0.0% 5.0% 10.0% 10.3% 5.8% 7.2% 9.7% Discount from original list, average

The average is 9.7% for homes over $439K and 10.3% for homes under $309K. It does not move in a straight line; homes under $309K 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

2026-11-03T07:12:44.817911 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% 82 53 41 53 94 53 65 53 76 83 61 83 Under $309K $309K–$357K $365K–$439K Over $439K

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

  • 83% of homes over $439K had a price cut before sale, against 82% of homes under $309K. Defined in 8.1.7.
  • 61% of homes over $439K had the seller pay closing costs or repairs, against 53% of homes under $309K. Defined in 8.1.8.
  • 83% of homes over $439K have a view, against 41% of homes under $309K. 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 $309K17 sales$309K–$357K17 sales$365K–$439K17 salesOver $439K18 salesAll69 salesReal difference?
Net sale price average$278,925$329,693$395,559$579,356$398,542by design
Net price per SF average$191$192$209$231$206unclear
Living area average1,4951,7401,8992,6321,951✓ large
Year built median20042009202020142014unclear

3.10 The numbers: selling

Under $309K17 sales$309K–$357K17 sales$365K–$439K17 salesOver $439K18 salesAll69 salesReal difference?
Days on market median100698014089unclear
Discount from original list average10.3%5.8%7.2%9.7%8.3%unclear
Price cut before sale82%53%65%83%71%unclear
Seller paid closing costs or repairs53%94%53%61%65%unclear
Has a view41%53%76%83%64%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 · 69 sales · November 3, 2025 – November 2, 2026

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

2026-11-03T07:12:44.838356 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 17 17 18 17 69 sales Sales per group Under 1,540 SF: 17 sales (25%) 1,540–1,817 SF: 17 sales (25%) 1,824–2,055 SF: 18 sales (26%) Over 2,055 SF: 17 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 1,540 SF1,540–1,817 SF1,824–2,055 SFOver 2,055 SF
Larger homes Over 2,055 SF
  • Sell for much more.
Smaller homes Under 1,540 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 1,540 SF1,540–1,817 SF1,824–2,055 SFOver 2,055 SFReal difference?
Net sale price$296KLowest$353K$390K$555KHighest✓ large
Net price per SF$216 per SF$209 per SF$202 per SF$198 per SFunclear
Year built2012200920202011unclear
Days on market76 days131 days56 days156 daysunclear
Discount from original list6.8%8.9%6.3%11.2%unclear
Price cut before sale71%76%56%82%unclear
Seller paid closing costs or repairs71%59%61%71%unclear
Has a view35%59%78%82%unclear

4.3 Homes over 2,055 SF sell for about $260K (88%) more than homes under 1,540 SF

2026-11-03T07:12:44.858886 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,540 SF 17 sales 1,540– 1,817 SF 17 sales 1,824– 2,055 SF 18 sales Over 2,055 SF 17 sales $0K $200K $400K $600K $296K $353K $390K $555K Net sale price, average

The average is $555K for homes over 2,055 SF and $296K for homes under 1,540 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

2026-11-03T07:12:44.882345 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,540 SF 17 sales 1,540– 1,817 SF 17 sales 1,824– 2,055 SF 18 sales Over 2,055 SF 17 sales $0 $100 $200 $216 $209 $202 $198 Net price per SF, average

The average is $198 per SF for homes over 2,055 SF and $216 per SF for homes under 1,540 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

2026-11-03T07:12:44.906953 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,540 SF 17 sales 1,540– 1,817 SF 17 sales 1,824– 2,055 SF 18 sales Over 2,055 SF 17 sales 1998 2004 2010 2016 2022 2012 2009 2020 2011 Year built: median (dot) and middle half (bar)

The median is 2011 for homes over 2,055 SF and 2012 for homes under 1,540 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

2026-11-03T07:12:44.930665 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,540 SF 17 sales 1,540– 1,817 SF 17 sales 1,824– 2,055 SF 18 sales Over 2,055 SF 17 sales 0 50 100 150 76 131 56 156 Days on market, median

The median is 156 days for homes over 2,055 SF and 76 days for homes under 1,540 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

2026-11-03T07:12:44.953218 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,540 SF 17 sales 1,540– 1,817 SF 17 sales 1,824– 2,055 SF 18 sales Over 2,055 SF 17 sales 0.0% 5.0% 10.0% 6.8% 8.9% 6.3% 11.2% Discount from original list, average

The average is 11.2% for homes over 2,055 SF and 6.8% for homes under 1,540 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

2026-11-03T07:12:44.979651 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% 71 71 35 76 59 59 56 61 78 82 71 82 Under 1,540 SF 1,540–1,817 SF 1,824–2,055 SF Over 2,055 SF

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

  • 82% of homes over 2,055 SF had a price cut before sale, against 71% of homes under 1,540 SF. Defined in 8.1.7.
  • 71% of homes over 2,055 SF had the seller pay closing costs or repairs, against 71% of homes under 1,540 SF. Defined in 8.1.8.
  • 82% of homes over 2,055 SF have a view, against 35% of homes under 1,540 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 1,540 SF17 sales1,540–1,817 SF17 sales1,824–2,055 SF18 salesOver 2,055 SF17 salesAll69 salesReal difference?
Net sale price average$295,713$353,118$390,413$555,402$398,542✓ large
Net price per SF average$216$209$202$198$206unclear
Living area average1,3831,6931,9352,7961,951by design
Year built median20122009202020112014unclear

4.10 The numbers: selling

Under 1,540 SF17 sales1,540–1,817 SF17 sales1,824–2,055 SF18 salesOver 2,055 SF17 salesAll69 salesReal difference?
Days on market median761315615689unclear
Discount from original list average6.8%8.9%6.3%11.2%8.3%unclear
Price cut before sale71%76%56%82%71%unclear
Seller paid closing costs or repairs71%59%61%71%65%unclear
Has a view35%59%78%82%64%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 · 69 sales · November 3, 2025 – November 2, 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.

2026-11-03T07:12:44.999898 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 17 17 18 17 69 sales Sales per group Before 2003: 17 sales (25%) 2003–2013: 17 sales (25%) 2014–2020: 18 sales (26%) After 2020: 17 sales (25%)
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$402K$399K$416Kunclear
Net price per SF$201 per SF$194 per SF$232 per SF$197 per SFunclear
Living area1,871 SF2,045 SF1,748 SF2,153 SFunclear
Days on market76 days89 days112 days79 daysunclear
Discount from original list8.5%10.6%6.7%7.5%unclear
Price cut before sale76%88%61%59%unclear
Seller paid closing costs or repairs59%71%61%71%unclear
Has a view71%59%72%53%unclear

5.3 Net sale price: no clear difference

2026-11-03T07:12:45.019916 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2013 17 sales 2014– 2020 18 sales After 2020 17 sales $0K $200K $400K $378K $402K $399K $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

2026-11-03T07:12:45.042677 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2013 17 sales 2014– 2020 18 sales After 2020 17 sales $0 $100 $200 $201 $194 $232 $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

2026-11-03T07:12:45.064295 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2013 17 sales 2014– 2020 18 sales After 2020 17 sales 0 1,000 2,000 1,871 2,045 1,748 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

2026-11-03T07:12:45.085480 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2013 17 sales 2014– 2020 18 sales After 2020 17 sales 0 50 100 76 89 112 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

2026-11-03T07:12:45.107876 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2013 17 sales 2014– 2020 18 sales After 2020 17 sales 0.0% 5.0% 10.0% 8.5% 10.6% 6.7% 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

2026-11-03T07:12:45.132854 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 88 71 59 61 61 72 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 sales2003–201317 sales2014–202018 salesAfter 202017 salesAll69 salesReal difference?
Net sale price average$377,859$402,033$398,569$415,706$398,542unclear
Net price per SF average$201$194$232$197$206unclear
Living area average1,8712,0451,7482,1531,951unclear
Year built median19962007201820222014by design

5.10 The numbers: selling

Before 200317 sales2003–201317 sales2014–202018 salesAfter 202017 salesAll69 salesReal difference?
Days on market median76891127989unclear
Discount from original list average8.5%10.6%6.7%7.5%8.3%unclear
Price cut before sale76%88%61%59%71%unclear
Seller paid closing costs or repairs59%71%61%71%65%unclear
Has a view71%59%72%53%64%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 · 69 sales · November 3, 2025 – November 2, 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.

2026-11-03T07:12:45.151078 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 44 24 68 sales Sales per group View: 44 sales (65%) No view: 24 sales (35%)
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$431KHighest$343KLowest✓ medium
Net price per SF$207 per SF$204 per SFunclear
Living area2,106 SFLargest1,692 SFSmallest✓ medium
Year built20142017unclear
Days on market87 days96 daysunclear
Discount from original list8.6%7.8%unclear
Price cut before sale66%79%unclear
Seller paid closing costs or repairs66%62%unclear

6.3 Homes with a view sell for about $88K (26%) more than homes without a view

2026-11-03T07:12:45.167395 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 44 sales No view 24 sales $0K $200K $400K $431K $343K Net sale price, average

The average is $431K 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

2026-11-03T07:12:45.185444 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 44 sales No view 24 sales $0 $50 $100 $150 $200 $207 $204 Net price per SF, average

The average is $207 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 410 SF (24%) larger than homes without a view

2026-11-03T07:12:45.229307 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 44 sales No view 24 sales 0 1,000 2,000 2,106 1,692 Living area (SF), average

The average is 2,106 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

2026-11-03T07:12:45.249099 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 44 sales No view 24 sales 2000 2005 2010 2015 2020 2014 2017 Year built: median (dot) and middle half (bar)

The median is 2014 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

2026-11-03T07:12:45.268185 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 44 sales No view 24 sales 0 25 50 75 100 87 96 Days on market, median

The median is 87 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

2026-11-03T07:12:45.288085 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 44 sales No view 24 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.6% 7.8% Discount from original list, average

The average is 8.6% 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

2026-11-03T07:12:45.307051 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 66 66 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.
  • 66% 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

View44 salesNo view24 salesAll68 salesReal difference?
Net sale price average$431,038$342,660$399,846✓ medium
Net price per SF average$207$204$206unclear
Living area average2,1061,6921,960✓ medium
Year built median201420172014unclear

6.11 The numbers: selling

View44 salesNo view24 salesAll68 salesReal difference?
Days on market median879690unclear
Discount from original list average8.6%7.8%8.3%unclear
Price cut before sale66%79%71%unclear
Seller paid closing costs or repairs66%62%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 8.3.4.

7. New constructionBasic statistics · 70 sales · November 3, 2025 – November 2, 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
69 resale sales. Average $398,542; median $365,000; standard deviation $133,696; middle half (25th–75th percentile) $309,000–$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
69 resale sales. Average $206; median $202; standard deviation $39; middle half (25th–75th percentile) $184–$220; 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
69 resale sales. Average 1,951; median 1,824; standard deviation 610; middle half (25th–75th percentile) 1,540–2,055; 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
69 resale sales. Average 2010; median 2014; standard deviation 12; 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
69 resale sales. Average 124; median 89; standard deviation 122; middle half (25th–75th percentile) 50–162; lowest 3, 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
69 resale sales. Average 8.3%; median 7.5%; standard deviation 5.7%; middle half (25th–75th percentile) 4.6%–10.4%; 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
49 of 69 resale sales (71.0%).

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 69 resale sales (65.2%).

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
44 sales with a view, 24 without, 1 unclassified. Most common View entries: Trees/Woods 36, Neighborhood 26, None 13, Panoramic 10, Rural 5, Park/Greenbelt 5, Golf Course 5, Pool 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 2026-11-03 13:00 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Bastrop, SubdivisionName contains any of “tahitian village”, “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 3, 2026: 141 closed Tahitian Village, records over the prior year, in ZIP 78602. 12 subdivision spellings kept: Tahitian Village, (87); 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 1 (1); Tahitian Village Unit 3 Reserve (1); Tahitian Village, Unit 1 (1); Tahitian Village, Unit 4 (1); Tahitian Village Unit 05 (1); Tahitian Village Unit 4 (1). 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 37 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 3, 2025 to November 2, 2026 inclusive.
The data
139 single-family sales in the window: 69 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
69 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 $309K”.
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 $309K: $248,000–$304,228 (17 sales); $309K–$357K: $309,000–$357,000 (17 sales); $365K–$439K: $365,000–$439,000 (17 sales); Over $439K: $440,000–$920,000 (18 sales)
Quartiles by living area: Under 1,540 SF: 1,233–1,527 SF (17 sales); 1,540–1,817 SF: 1,540–1,817 SF (17 sales); 1,824–2,055 SF: 1,824–2,055 SF (18 sales); Over 2,055 SF: 2,060–4,050 SF (17 sales)
Quartiles by year built: Before 2003: 1978–2002 (17 sales); 2003–2013: 2003–2013 (17 sales); 2014–2020: 2014–2020 (18 sales); After 2020: 2021–2025 (17 sales)
View and no view: View: MLS lists a view (44 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 $398,542, median $365,000. Days on market: average 124, 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 = 9.9630.0189p < 0.0063Unclearε² = 0.147large
Living areaKruskal–WallisH = 34.663< 0.0001p < 0.0063Yesε² = 0.510large
Year builtKruskal–WallisH = 11.5030.0093p < 0.0063Unclearε² = 0.169large
Days on marketKruskal–WallisH = 6.9830.0725p < 0.0063Unclearε² = 0.103medium
Discount from original listKruskal–WallisH = 7.1230.0683p < 0.0063Unclearε² = 0.105medium
Price cut before saleChi-squareχ² = 5.4230.1438p < 0.0063UnclearCramér’s V = 0.280small
Seller paid closing costs or repairsChi-squareχ² = 8.6530.0343p < 0.0063UnclearCramér’s V = 0.354medium
Has a viewChi-squareχ² = 8.7930.0323p < 0.0063UnclearCramér’s V = 0.357medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 39.673< 0.0001p < 0.0063Yesε² = 0.583large
Net price per SFKruskal–WallisH = 1.7930.6164p < 0.0063Unclearε² = 0.026small
Year builtKruskal–WallisH = 9.7530.0208p < 0.0063Unclearε² = 0.143large
Days on marketKruskal–WallisH = 8.0730.0447p < 0.0063Unclearε² = 0.119medium
Discount from original listKruskal–WallisH = 8.0630.0449p < 0.0063Unclearε² = 0.118medium
Price cut before saleChi-squareχ² = 3.4030.3341p < 0.0063UnclearCramér’s V = 0.222small
Seller paid closing costs or repairsChi-squareχ² = 0.8730.8321p < 0.0063UnclearCramér’s V = 0.112small
Has a viewChi-squareχ² = 10.2230.0168p < 0.0063UnclearCramér’s V = 0.385medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.2730.1533p < 0.0063Unclearε² = 0.077medium
Net price per SFKruskal–WallisH = 7.4330.0593p < 0.0063Unclearε² = 0.109medium
Living areaKruskal–WallisH = 4.1930.2418p < 0.0063Unclearε² = 0.062medium
Days on marketKruskal–WallisH = 0.7730.8556p < 0.0063Unclearε² = 0.011small
Discount from original listKruskal–WallisH = 4.7230.1935p < 0.0063Unclearε² = 0.069medium
Price cut before saleChi-squareχ² = 4.7830.1886p < 0.0063UnclearCramér’s V = 0.263small
Seller paid closing costs or repairsChi-squareχ² = 0.8730.8321p < 0.0063UnclearCramér’s V = 0.112small
Has a viewChi-squareχ² = 1.9430.5846p < 0.0063UnclearCramér’s V = 0.168small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 757.50—0.0033p < 0.0063Yesrank-biserial r = 0.435medium
Net price per SFMann–Whitney UU = 578.00—0.5253p < 0.0063Unclearrank-biserial r = 0.095negligible
Living areaMann–Whitney UU = 764.00—0.0025p < 0.0063Yesrank-biserial r = 0.447medium
Year builtMann–Whitney UU = 447.50—0.3039p < 0.0063Unclearrank-biserial r = 0.152small
Days on marketMann–Whitney UU = 525.50—0.9795p < 0.0063Unclearrank-biserial r = 0.005negligible
Discount from original listMann–Whitney UU = 591.00—0.4225p < 0.0063Unclearrank-biserial r = 0.119small
Price cut before saleChi-squareχ² = 1.3110.2515p < 0.0063UnclearCramér’s V = 0.139small
Seller paid closing costs or repairsChi-squareχ² = 0.0810.7786p < 0.0063UnclearCramér’s V = 0.034negligible

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 69 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 3, 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.