ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Mason Ranch

Leander, TX 78641
Resale homes · closed Nov 9 – Nov 8, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 9, 2026 · 5:01 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
29
single-family resale homes
Median net sale price
$490,000
average $532,645
Median net price per SF
$181
average $190
Median days on market
63 days
average 115 days
1. SummaryResale homes · 29 sales · November 9, 2025 – November 8, 2026

This study looks at the 29 resale homes sold in Mason Ranch in the 365 days to November 8, 2026. A full year is used because only 16 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 sold29 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 $452K · 7 sales$452K–$485K · 7 sales$490K–$570K · 8 salesOver $570K · 7 sales
3. Quartiles by net sale priceResale homes · 29 sales · November 9, 2025 – November 8, 2026

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

2026-11-09T05:01:44.181786 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under $452K: 7 sales (24%) $452K–$485K: 7 sales (24%) $490K–$570K: 8 sales (28%) Over $570K: 7 sales (24%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

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 $452K$452K–$485K$490K–$570KOver $570KReal difference?
Net price per SF$162 per SF$182 per SF$176 per SF$242 per SFunclear
Living area2,486 SF2,673 SF3,081 SF3,067 SFunclear
Year built2016201720172018unclear
Days on market176 days48 days56 days53 daysunclear
Discount from original list11.3%7.1%3.5%3.1%unclear
Price cut before sale86%43%38%43%unclear
Seller paid closing costs or repairs71%71%75%57%unclear
Has a view0%43%38%29%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

2026-11-09T05:01:44.210489 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $452K 7 sales $452K– $485K 7 sales $490K– $570K 8 sales Over $570K 7 sales $0 $100 $200 $162 $182 $176 $242 Net price per SF, average

The average is $242 per SF for homes over $570K and $162 per SF for homes under $452K. It does not move in a straight line; homes over $570K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-11-09T05:01:44.232569 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $452K 7 sales $452K– $485K 7 sales $490K– $570K 8 sales Over $570K 7 sales 0 1,000 2,000 3,000 2,486 2,673 3,081 3,067 Living area (SF), average

The average is 3,067 SF for homes over $570K and 2,486 SF for homes under $452K. It does not move in a straight line; homes $490K–$570K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-11-09T05:01:44.256404 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $452K 7 sales $452K– $485K 7 sales $490K– $570K 8 sales Over $570K 7 sales 2016 2017 2018 2019 2016 2017 2017 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over $570K and 2016 for homes under $452K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-09T05:01:44.278838 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $452K 7 sales $452K– $485K 7 sales $490K– $570K 8 sales Over $570K 7 sales 0 100 200 176 48 56 53 Days on market, median

The median is 53 days for homes over $570K and 176 days for homes under $452K. It does not move in a straight line; homes under $452K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-09T05:01:44.300446 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $452K 7 sales $452K– $485K 7 sales $490K– $570K 8 sales Over $570K 7 sales 0.0% 5.0% 10.0% 11.3% 7.1% 3.5% 3.1% Discount from original list, average

The average is 3.1% for homes over $570K and 11.3% for homes under $452K. It falls step by step from the lowest range to the 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

2026-11-09T05:01:44.328991 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% 86% 71% 0% 43% 71% 43% 38% 75% 38% 43% 57% 29% Under $452K $452K–$485K $490K–$570K Over $570K

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

  • 43% of homes over $570K had a price cut before sale, against 86% of homes under $452K. Defined in 8.1.7.
  • 57% of homes over $570K had the seller pay closing costs or repairs, against 71% of homes under $452K. Defined in 8.1.8.
  • 29% of homes over $570K have a view, against 0% of homes under $452K. 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 $452K7 sales$452K–$485K7 sales$490K–$570K8 salesOver $570K7 salesAll29 salesReal difference?
Net sale price average$396,044$470,829$537,212$725,843$532,645by design
Net price per SF average$162$182$176$242$190unclear
Living area average2,4862,6733,0813,0672,835unclear
Year built median20162017201720182018unclear

3.10 The numbers: selling

Under $452K7 sales$452K–$485K7 sales$490K–$570K8 salesOver $570K7 salesAll29 salesReal difference?
Days on market median17648565363unclear
Discount from original list average11.3%7.1%3.5%3.1%6.1%unclear
Price cut before sale86%43%38%43%52%unclear
Seller paid closing costs or repairs71%71%75%57%69%unclear
Has a view0%43%38%29%28%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 · 29 sales · November 9, 2025 – November 8, 2026

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

2026-11-09T05:01:44.349067 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under 2,557 SF: 7 sales (24%) 2,557–2,737 SF: 7 sales (24%) 2,745–3,171 SF: 8 sales (28%) Over 3,171 SF: 7 sales (24%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

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

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 2,557 SF2,557–2,737 SF2,745–3,171 SFOver 3,171 SFReal difference?
Net sale price$449K$520K$568K$588Kunclear
Net price per SF$205 per SF$196 per SF$193 per SF$166 per SFunclear
Year built2018201720192018unclear
Days on market48 days63 days60 days84 daysunclear
Discount from original list6.2%6.0%9.7%2.2%unclear
Price cut before sale43%43%75%43%unclear
Seller paid closing costs or repairs57%71%75%71%unclear
Has a view29%14%38%29%unclear

4.3 Net sale price: no clear difference

2026-11-09T05:01:44.369327 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,557 SF 7 sales 2,557– 2,737 SF 7 sales 2,745– 3,171 SF 8 sales Over 3,171 SF 7 sales $0K $200K $400K $600K $449K $520K $568K $588K Net sale price, average

The average is $588K for homes over 3,171 SF and $449K for homes under 2,557 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-11-09T05:01:44.391899 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,557 SF 7 sales 2,557– 2,737 SF 7 sales 2,745– 3,171 SF 8 sales Over 3,171 SF 7 sales $0 $100 $200 $205 $196 $193 $166 Net price per SF, average

The average is $166 per SF for homes over 3,171 SF and $205 per SF for homes under 2,557 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

2026-11-09T05:01:44.416030 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,557 SF 7 sales 2,557– 2,737 SF 7 sales 2,745– 3,171 SF 8 sales Over 3,171 SF 7 sales 2016 2017 2018 2019 2020 2018 2017 2019 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over 3,171 SF and 2018 for homes under 2,557 SF. It does not move in a straight line; homes 2,745–3,171 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-09T05:01:44.439258 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,557 SF 7 sales 2,557– 2,737 SF 7 sales 2,745– 3,171 SF 8 sales Over 3,171 SF 7 sales 0 50 100 48 63 60 84 Days on market, median

The median is 84 days for homes over 3,171 SF and 48 days for homes under 2,557 SF. It does not move in a straight line; homes over 3,171 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-09T05:01:44.460965 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,557 SF 7 sales 2,557– 2,737 SF 7 sales 2,745– 3,171 SF 8 sales Over 3,171 SF 7 sales 0.0% 5.0% 10.0% 6.2% 6.0% 9.7% 2.2% Discount from original list, average

The average is 2.2% for homes over 3,171 SF and 6.2% for homes under 2,557 SF. It does not move in a straight line; homes 2,745–3,171 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

2026-11-09T05:01:44.486628 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% 43% 57% 29% 43% 71% 14% 75% 75% 38% 43% 71% 29% Under 2,557 SF 2,557–2,737 SF 2,745–3,171 SF Over 3,171 SF

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

  • 43% of homes over 3,171 SF had a price cut before sale, against 43% of homes under 2,557 SF. Defined in 8.1.7.
  • 71% of homes over 3,171 SF had the seller pay closing costs or repairs, against 57% of homes under 2,557 SF. Defined in 8.1.8.
  • 29% of homes over 3,171 SF have a view, against 29% of homes under 2,557 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 2,557 SF7 sales2,557–2,737 SF7 sales2,745–3,171 SF8 salesOver 3,171 SF7 salesAll29 salesReal difference?
Net sale price average$449,280$520,214$568,388$587,593$532,645unclear
Net price per SF average$205$196$193$166$190unclear
Living area average2,1992,6562,9513,5182,835by design
Year built median20182017201920182018unclear

4.10 The numbers: selling

Under 2,557 SF7 sales2,557–2,737 SF7 sales2,745–3,171 SF8 salesOver 3,171 SF7 salesAll29 salesReal difference?
Days on market median4863608463unclear
Discount from original list average6.2%6.0%9.7%2.2%6.1%unclear
Price cut before sale43%43%75%43%52%unclear
Seller paid closing costs or repairs57%71%75%71%69%unclear
Has a view29%14%38%29%28%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 · 29 sales · November 9, 2025 – November 8, 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.

2026-11-09T05:01:44.506745 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 5 9 6 29 sales Sales per group Before 2017: 9 sales (31%) 2017: 5 sales (17%) 2018–2019: 9 sales (31%) After 2019: 6 sales (21%)
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 201720172018–2019After 2019Real difference?
Net sale price$448K$546K$605K$539Kunclear
Net price per SF$169 per SF$211 per SF$206 per SF$179 per SFunclear
Living area2,698 SF2,604 SF2,951 SF3,062 SFunclear
Days on market81 days13 days63 days48 daysunclear
Discount from original list10.1%4.5%3.7%5.1%unclear
Price cut before sale78%20%56%33%unclear
Seller paid closing costs or repairs56%60%78%83%unclear
Has a view22%40%11%50%unclear

5.3 Net sale price: no clear difference

2026-11-09T05:01:44.526784 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 9 sales 2017 5 sales 2018– 2019 9 sales After 2019 6 sales $0K $200K $400K $600K $448K $546K $605K $539K Net sale price, average

The average is $539K for homes built after 2019 and $448K for homes built before 2017. It does not move in a straight line; homes built 2018–2019 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-09T05:01:44.549465 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 9 sales 2017 5 sales 2018– 2019 9 sales After 2019 6 sales $0 $100 $200 $169 $211 $206 $179 Net price per SF, average

The average is $179 per SF for homes built after 2019 and $169 per SF for homes built before 2017. It does not move in a straight line; homes built 2017 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-09T05:01:44.570328 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 9 sales 2017 5 sales 2018– 2019 9 sales After 2019 6 sales 0 1,000 2,000 3,000 2,698 2,604 2,951 3,062 Living area (SF), average

The average is 3,062 SF for homes built after 2019 and 2,698 SF for homes built before 2017. It does not move in a straight line; homes built after 2019 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-09T05:01:44.591757 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 9 sales 2017 5 sales 2018– 2019 9 sales After 2019 6 sales 0 25 50 75 81 13 63 48 Days on market, median

The median is 48 days for homes built after 2019 and 81 days for homes built before 2017. It does not move in a straight line; homes built before 2017 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-09T05:01:44.613813 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 9 sales 2017 5 sales 2018– 2019 9 sales After 2019 6 sales 0.0% 5.0% 10.0% 10.1% 4.5% 3.7% 5.1% Discount from original list, average

The average is 5.1% for homes built after 2019 and 10.1% for homes built before 2017. It does not move in a straight line; homes built before 2017 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

2026-11-09T05:01:44.637928 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% 56% 22% 20% 60% 40% 56% 78% 11% 33% 83% 50% Before 2017 2017 2018–2019 After 2019

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

  • 33% of homes built after 2019 had a price cut before sale, against 78% of homes built before 2017. Defined in 8.1.7.
  • 83% of homes built after 2019 had the seller pay closing costs or repairs, against 56% of homes built before 2017. Defined in 8.1.8.
  • 50% of homes built after 2019 have a view, against 22% of homes built before 2017. 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 20179 sales20175 sales2018–20199 salesAfter 20196 salesAll29 salesReal difference?
Net sale price average$448,328$546,200$605,479$538,575$532,645unclear
Net price per SF average$169$211$206$179$190unclear
Living area average2,6982,6042,9513,0622,835unclear
Year built median20162017201920202018by design

5.10 The numbers: selling

Before 20179 sales20175 sales2018–20199 salesAfter 20196 salesAll29 salesReal difference?
Days on market median8113634863unclear
Discount from original list average10.1%4.5%3.7%5.1%6.1%unclear
Price cut before sale78%20%56%33%52%unclear
Seller paid closing costs or repairs56%60%78%83%69%unclear
Has a view22%40%11%50%28%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 · 29 sales · November 9, 2025 – November 8, 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.

2026-11-09T05:01:44.655816 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 20 28 sales Sales per group View: 8 sales (29%) No view: 20 sales (71%)
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 less likely to need a price cut.
Homes without a view no view listed
  • Are more likely to have had a price cut.

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$592K$516Kunclear
Net price per SF$213 per SF$180 per SFunclear
Living area2,832 SF2,881 SFunclear
Year built20182018unclear
Days on market38 days76 daysunclear
Discount from original list4.1%7.1%unclear
Price cut before sale12%Fewest70%Most✓ large
Seller paid closing costs or repairs62%70%unclear

6.3 Net sale price: no clear difference

2026-11-09T05:01:44.671466 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales $0K $200K $400K $600K $592K $516K Net sale price, average

The average is $592K for homes with a view and $516K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-11-09T05:01:44.689148 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales $0 $100 $200 $213 $180 Net price per SF, average

The average is $213 per SF for homes with a view and $180 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-11-09T05:01:44.706912 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 0 1,000 2,000 3,000 2,832 2,881 Living area (SF), average

The average is 2,832 SF for homes with a view and 2,881 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-09T05:01:44.748430 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 2016 2017 2018 2019 2020 2018 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes with a view and 2018 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-09T05:01:44.767010 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 0 20 40 60 80 38 76 Days on market, median

The median is 38 days for homes with a view and 76 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

2026-11-09T05:01:44.785929 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 0.0% 2.0% 4.0% 6.0% 8.0% 4.1% 7.1% Discount from original list, average

The average is 4.1% for homes with a view and 7.1% 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

2026-11-09T05:01:44.803760 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 12% 62% 70% 70% View No view

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

  • 12% of homes with a view had a price cut before sale, against 70% 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 70% of homes without a view. Defined in 8.1.8.
Price cut before sale: ✓ Real difference · large
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View8 salesNo view20 salesAll28 salesReal difference?
Net sale price average$592,400$516,026$537,847unclear
Net price per SF average$213$180$190unclear
Living area average2,8322,8812,867unclear
Year built median201820182018unclear

6.11 The numbers: selling

View8 salesNo view20 salesAll28 salesReal difference?
Days on market median387664unclear
Discount from original list average4.1%7.1%6.3%unclear
Price cut before sale12%70%54%✓ large
Seller paid closing costs or repairs62%70%68%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 · 0 sales · November 9, 2025 – November 8, 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: 0 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 Mason Ranch.

No new-construction sales were reported in ABOR MLS in this window.

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
29 resale sales. Average $532,645; median $490,000; standard deviation $131,913; middle half (25th–75th percentile) $452,500–$570,000; lowest $350,000, highest $888,050. 20 sales had a seller payment; their median payment was $5,600.

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
29 resale sales. Average $190; median $181; standard deviation $42; middle half (25th–75th percentile) $161–$205; lowest $132, highest $283.

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
29 resale sales. Average 2,835; median 2,745; standard deviation 520; middle half (25th–75th percentile) 2,557–3,171; lowest 1,944, highest 4,030.

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
29 resale sales. Average 2018; median 2018; standard deviation 2; middle half (25th–75th percentile) 2016–2019; lowest 2014, highest 2021.

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
29 resale sales. Average 115; median 63; standard deviation 154; middle half (25th–75th percentile) 27–109; lowest 5, highest 553. 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
29 resale sales. Average 6.1%; median 4.2%; standard deviation 6.1%; middle half (25th–75th percentile) 2.0%–8.3%; lowest −2.6%, highest 20.6%. 2 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
15 of 29 resale sales (51.7%).

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
20 of 29 resale sales (69.0%).

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
8 sales with a view, 20 without, 1 unclassified. Most common View entries: None 16, Neighborhood 6, Park/Greenbelt 4, Trees/Woods 4, Pool 2, Garden 1, Pond 1, Water 1.

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 2026-11-09 11:00 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Leander, SubdivisionName contains any of “mason ranch”, “mason hills” (case-insensitive). A record is kept when its subdivision name belongs to the Mason Ranch family, the same rule comparable sales use (it includes Mason Hills, proven adjacent and priced alike).
The data
Pulled November 9, 2026: 29 closed Mason Ranch records over the prior year, in ZIP 78641. 12 subdivision spellings kept: Mason Hills (6); Mason Ranch (5); Mason Ranch Ph 1 Sec 1 (3); Mason Ranch Ph 1 Sec 4 (3); Mason Ranch Ph 2 Sec 1 (3); Mason Ranch Ph 1 Sec 7 & Sec 8 (2); Mason Ranch Ph 2 Sec 2A (2); Mason Ranch Ph 1 Sec 5 (1); MASON RANCH (1); Mason Ranch Ph 1 Sec 2 (1); Mason Ranch Ph 1 Sec 7 (1); MASON RANCH PH 2 SEC 1 (1). Names found by the search but not part of Mason Ranch, left out: The Groves at Mason Hills (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 16 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 9, 2025 to November 8, 2026 inclusive.
The data
29 single-family sales in the window: 29 resale, 0 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
29 resale; 0 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
None in this window.

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 $452K”.
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 $452K: $350,000–$451,500 (7 sales); $452K–$485K: $452,500–$485,000 (7 sales); $490K–$570K: $490,000–$570,000 (8 sales); Over $570K: $580,000–$888,050 (7 sales)
Quartiles by living area: Under 2,557 SF: 1,944–2,480 SF (7 sales); 2,557–2,737 SF: 2,557–2,737 SF (7 sales); 2,745–3,171 SF: 2,745–3,171 SF (8 sales); Over 3,171 SF: 3,229–4,030 SF (7 sales)
Quartiles by year built: Before 2017: 2014–2016 (9 sales); 2017: 2017–2017 (5 sales); 2018–2019: 2018–2019 (9 sales); After 2019: 2020–2021 (6 sales)
View and no view: View: MLS lists a view (8 sales); No view: None or Neighborhood (20 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 $532,645, median $490,000. Days on market: average 115, median 63: 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
1 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 = 11.6130.0089p < 0.0063Unclearε² = 0.414large
Living areaKruskal–WallisH = 6.6330.0846p < 0.0063Unclearε² = 0.237large
Year builtKruskal–WallisH = 1.8830.5980p < 0.0063Unclearε² = 0.067medium
Days on marketKruskal–WallisH = 2.0930.5536p < 0.0063Unclearε² = 0.075medium
Discount from original listKruskal–WallisH = 7.9330.0476p < 0.0063Unclearε² = 0.283large
Price cut before saleChi-squareχ² = 4.3330.2282p < 0.0063UnclearCramér’s V = 0.386medium
Seller paid closing costs or repairsChi-squareχ² = 0.6330.8889p < 0.0063UnclearCramér’s V = 0.148small
Has a viewChi-squareχ² = 3.8830.2746p < 0.0063UnclearCramér’s V = 0.366medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 6.3030.0980p < 0.0063Unclearε² = 0.225large
Net price per SFKruskal–WallisH = 4.1830.2428p < 0.0063Unclearε² = 0.149large
Year builtKruskal–WallisH = 4.0730.2538p < 0.0063Unclearε² = 0.145large
Days on marketKruskal–WallisH = 0.8230.8457p < 0.0063Unclearε² = 0.029small
Discount from original listKruskal–WallisH = 6.1430.1051p < 0.0063Unclearε² = 0.219large
Price cut before saleChi-squareχ² = 2.4030.4942p < 0.0063UnclearCramér’s V = 0.287small
Seller paid closing costs or repairsChi-squareχ² = 0.6330.8889p < 0.0063UnclearCramér’s V = 0.148small
Has a viewChi-squareχ² = 1.0230.7963p < 0.0063UnclearCramér’s V = 0.188small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 6.4530.0916p < 0.0063Unclearε² = 0.230large
Net price per SFKruskal–WallisH = 8.4330.0379p < 0.0063Unclearε² = 0.301large
Living areaKruskal–WallisH = 3.1330.3724p < 0.0063Unclearε² = 0.112medium
Days on marketKruskal–WallisH = 2.7030.4397p < 0.0063Unclearε² = 0.097medium
Discount from original listKruskal–WallisH = 6.2730.0990p < 0.0063Unclearε² = 0.224large
Price cut before saleChi-squareχ² = 5.3330.1493p < 0.0063UnclearCramér’s V = 0.429medium
Seller paid closing costs or repairsChi-squareχ² = 1.8530.6043p < 0.0063UnclearCramér’s V = 0.253small
Has a viewChi-squareχ² = 3.2530.3551p < 0.0063UnclearCramér’s V = 0.335medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 106.00—0.1991p < 0.0063Unclearrank-biserial r = 0.325medium
Net price per SFMann–Whitney UU = 112.00—0.1103p < 0.0063Unclearrank-biserial r = 0.400medium
Living areaMann–Whitney UU = 81.00—0.9801p < 0.0063Unclearrank-biserial r = 0.012negligible
Year builtMann–Whitney UU = 96.00—0.4252p < 0.0063Unclearrank-biserial r = 0.200small
Days on marketMann–Whitney UU = 49.50—0.1268p < 0.0063Unclearrank-biserial r = 0.381medium
Discount from original listMann–Whitney UU = 50.00—0.1358p < 0.0063Unclearrank-biserial r = 0.375medium
Price cut before saleChi-squareχ² = 7.6010.0059p < 0.0063YesCramér’s V = 0.521large
Seller paid closing costs or repairsChi-squareχ² = 0.1510.7011p < 0.0063UnclearCramér’s V = 0.073negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); nothing else. 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 29 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 9, 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.