ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Stone Canyon

Round Rock, TX 78681
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 5:43 AM CDT
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
33
single-family resale homes
Median net sale price
$544,497
average $590,273
Median net price per SF
$214
average $214
Median days on market
25 days
average 55 days
1. SummaryResale homes · 33 sales · October 26, 2025 – October 25, 2026

This study looks at the 33 resale homes sold in Stone Canyon in the 365 days to October 25, 2026. A full year is used because only 17 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 sold33 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 $511K · 8 sales$511K–$531K · 8 sales$544K–$680K · 9 salesOver $680K · 8 sales
3. Quartiles by net sale priceResale homes · 33 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T05:44:02.963001 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 9 8 33 sales Sales per group Under $511K: 8 sales (24%) $511K–$531K: 8 sales (24%) $544K–$680K: 9 sales (27%) Over $680K: 8 sales (24%)
Bottom line

3.1 Key differences

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

Under $511K$511K–$531K$544K–$680KOver $680K
Higher-priced homes Over $680K
  • Are much larger.
Lower-priced homes Under $511K
  • 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 $511K$511K–$531K$544K–$680KOver $680KReal difference?
Net price per SF$205 per SF$199 per SF$219 per SF$234 per SFunclear
Living area2,259 SFSmallest2,635 SF2,816 SF3,302 SFLargest✓ large
Year built2000199919992000unclear
Days on market28 days33 days39 days10 daysunclear
Discount from original list7.2%6.0%4.9%3.9%unclear
Price cut before sale38%62%56%25%unclear
Seller paid closing costs or repairs75%62%56%75%unclear
Has a view25%25%33%50%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

2026-10-26T05:44:02.991661 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $511K 8 sales $511K– $531K 8 sales $544K– $680K 9 sales Over $680K 8 sales $0 $100 $200 $205 $199 $219 $234 Net price per SF, average

The average is $234 per SF for homes over $680K and $205 per SF for homes under $511K. It does not move in a straight line; homes over $680K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $680K are about 1,040 SF (46%) larger than homes under $511K

2026-10-26T05:44:03.013930 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $511K 8 sales $511K– $531K 8 sales $544K– $680K 9 sales Over $680K 8 sales 0 1,000 2,000 3,000 2,259 2,635 2,816 3,302 Living area (SF), average

The average is 3,302 SF for homes over $680K and 2,259 SF for homes under $511K. 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

2026-10-26T05:44:03.037117 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $511K 8 sales $511K– $531K 8 sales $544K– $680K 9 sales Over $680K 8 sales 1998 1999 2000 2000 1999 1999 2000 Year built: median (dot) and middle half (bar)

The median is 2000 for homes over $680K and 2000 for homes under $511K. It does not move in a straight line; homes under $511K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:44:03.059481 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $511K 8 sales $511K– $531K 8 sales $544K– $680K 9 sales Over $680K 8 sales 0 20 40 28 33 39 10 Days on market, median

The median is 10 days for homes over $680K and 28 days for homes under $511K. It does not move in a straight line; homes $544K–$680K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:44:03.081760 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $511K 8 sales $511K– $531K 8 sales $544K– $680K 9 sales Over $680K 8 sales 0.0% 2.5% 5.0% 7.5% 7.2% 6.0% 4.9% 3.9% Discount from original list, average

The average is 3.9% for homes over $680K and 7.2% for homes under $511K. 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

2026-10-26T05:44:03.111799 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% 38 75 25 62 62 25 56 56 33 25 75 50 Under $511K $511K–$531K $544K–$680K Over $680K

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

  • 25% of homes over $680K had a price cut before sale, against 38% of homes under $511K. Defined in 8.1.7.
  • 75% of homes over $680K had the seller pay closing costs or repairs, against 75% of homes under $511K. Defined in 8.1.8.
  • 50% of homes over $680K have a view, against 25% of homes under $511K. 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 $511K8 sales$511K–$531K8 sales$544K–$680K9 salesOver $680K8 salesAll33 salesReal difference?
Net sale price average$456,896$521,316$612,741$767,331$590,273by design
Net price per SF average$205$199$219$234$214unclear
Living area average2,2592,6352,8163,3022,755✓ large
Year built median20001999199920001999unclear

3.10 The numbers: selling

Under $511K8 sales$511K–$531K8 sales$544K–$680K9 salesOver $680K8 salesAll33 salesReal difference?
Days on market median2833391025unclear
Discount from original list average7.2%6.0%4.9%3.9%5.5%unclear
Price cut before sale38%62%56%25%45%unclear
Seller paid closing costs or repairs75%62%56%75%67%unclear
Has a view25%25%33%50%33%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 · 33 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T05:44:03.132377 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 9 8 33 sales Sales per group Under 2,453 SF: 8 sales (24%) 2,453–2,685 SF: 8 sales (24%) 2,714–3,065 SF: 9 sales (27%) Over 3,065 SF: 8 sales (24%)
Bottom line

4.1 Key differences

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

Under 2,453 SF2,453–2,685 SF2,714–3,065 SFOver 3,065 SF
Larger homes Over 3,065 SF
  • Sell for much more.
Smaller homes Under 2,453 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 2,453 SF2,453–2,685 SF2,714–3,065 SFOver 3,065 SFReal difference?
Net sale price$478KLowest$552K$580K$752KHighest✓ large
Net price per SF$218 per SF$219 per SF$203 per SF$219 per SFunclear
Year built2000199919991999unclear
Days on market61 days18 days12 days24 daysunclear
Discount from original list4.7%4.0%7.3%5.7%unclear
Price cut before sale50%38%44%50%unclear
Seller paid closing costs or repairs88%38%67%75%unclear
Has a view38%38%11%50%unclear

4.3 Homes over 3,065 SF sell for about $275K (58%) more than homes under 2,453 SF

2026-10-26T05:44:03.153501 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,453 SF 8 sales 2,453– 2,685 SF 8 sales 2,714– 3,065 SF 9 sales Over 3,065 SF 8 sales $0K $250K $500K $750K $478K $552K $580K $752K Net sale price, average

The average is $752K for homes over 3,065 SF and $478K for homes under 2,453 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

2026-10-26T05:44:03.176790 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,453 SF 8 sales 2,453– 2,685 SF 8 sales 2,714– 3,065 SF 9 sales Over 3,065 SF 8 sales $0 $100 $200 $218 $219 $203 $219 Net price per SF, average

The average is $219 per SF for homes over 3,065 SF and $218 per SF for homes under 2,453 SF. It does not move in a straight line; homes over 3,065 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T05:44:03.200375 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,453 SF 8 sales 2,453– 2,685 SF 8 sales 2,714– 3,065 SF 9 sales Over 3,065 SF 8 sales 1998 1999 2000 2001 2000 1999 1999 1999 Year built: median (dot) and middle half (bar)

The median is 1999 for homes over 3,065 SF and 2000 for homes under 2,453 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:44:03.223301 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,453 SF 8 sales 2,453– 2,685 SF 8 sales 2,714– 3,065 SF 9 sales Over 3,065 SF 8 sales 0 20 40 60 61 18 12 24 Days on market, median

The median is 24 days for homes over 3,065 SF and 61 days for homes under 2,453 SF. It does not move in a straight line; homes under 2,453 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:44:03.246342 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,453 SF 8 sales 2,453– 2,685 SF 8 sales 2,714– 3,065 SF 9 sales Over 3,065 SF 8 sales 0.0% 2.5% 5.0% 7.5% 4.7% 4.0% 7.3% 5.7% Discount from original list, average

The average is 5.7% for homes over 3,065 SF and 4.7% for homes under 2,453 SF. It does not move in a straight line; homes 2,714–3,065 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

2026-10-26T05:44:03.273212 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% 50 88 38 38 38 38 44 67 11 50 75 50 Under 2,453 SF 2,453–2,685 SF 2,714–3,065 SF Over 3,065 SF

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

  • 50% of homes over 3,065 SF had a price cut before sale, against 50% of homes under 2,453 SF. Defined in 8.1.7.
  • 75% of homes over 3,065 SF had the seller pay closing costs or repairs, against 88% of homes under 2,453 SF. Defined in 8.1.8.
  • 50% of homes over 3,065 SF have a view, against 38% of homes under 2,453 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 2,453 SF8 sales2,453–2,685 SF8 sales2,714–3,065 SF9 salesOver 3,065 SF8 salesAll33 salesReal difference?
Net sale price average$477,726$551,854$580,303$752,456$590,273✓ large
Net price per SF average$218$219$203$219$214unclear
Living area average2,2042,5262,8553,4222,755by design
Year built median20001999199919991999unclear

4.10 The numbers: selling

Under 2,453 SF8 sales2,453–2,685 SF8 sales2,714–3,065 SF9 salesOver 3,065 SF8 salesAll33 salesReal difference?
Days on market median6118122425unclear
Discount from original list average4.7%4.0%7.3%5.7%5.5%unclear
Price cut before sale50%38%44%50%45%unclear
Seller paid closing costs or repairs88%38%67%75%67%unclear
Has a view38%38%11%50%33%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 · 33 sales · October 26, 2025 – October 25, 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.

2026-10-26T05:44:03.293579 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 8 5 33 sales Sales per group Before 1999: 10 sales (30%) 1999: 10 sales (30%) 2000: 8 sales (24%) After 2000: 5 sales (15%)
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 199919992000After 2000Real difference?
Net sale price$602K$564K$590K$619Kunclear
Net price per SF$213 per SF$208 per SF$218 per SF$225 per SFunclear
Living area2,848 SF2,716 SF2,692 SF2,748 SFunclear
Days on market30 days18 days32 days14 daysunclear
Discount from original list5.3%5.8%6.1%4.2%unclear
Price cut before sale50%30%62%40%unclear
Seller paid closing costs or repairs70%60%50%100%unclear
Has a view30%20%38%60%unclear

5.3 Net sale price: no clear difference

2026-10-26T05:44:03.313637 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 10 sales 1999 10 sales 2000 8 sales After 2000 5 sales $0K $200K $400K $600K $602K $564K $590K $619K Net sale price, average

The average is $619K for homes built after 2000 and $602K for homes built before 1999. It does not move in a straight line; homes built after 2000 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T05:44:03.336516 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 10 sales 1999 10 sales 2000 8 sales After 2000 5 sales $0 $100 $200 $213 $208 $218 $225 Net price per SF, average

The average is $225 per SF for homes built after 2000 and $213 per SF for homes built before 1999. It does not move in a straight line; homes built after 2000 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T05:44:03.357627 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 10 sales 1999 10 sales 2000 8 sales After 2000 5 sales 0 1,000 2,000 3,000 2,848 2,716 2,692 2,748 Living area (SF), average

The average is 2,748 SF for homes built after 2000 and 2,848 SF for homes built before 1999. It does not move in a straight line; homes built before 1999 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T05:44:03.378686 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 10 sales 1999 10 sales 2000 8 sales After 2000 5 sales 0 10 20 30 30 18 32 14 Days on market, median

The median is 14 days for homes built after 2000 and 30 days for homes built before 1999. It does not move in a straight line; homes built 2000 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T05:44:03.400994 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 10 sales 1999 10 sales 2000 8 sales After 2000 5 sales 0.0% 2.0% 4.0% 6.0% 5.3% 5.8% 6.1% 4.2% Discount from original list, average

The average is 4.2% for homes built after 2000 and 5.3% for homes built before 1999. It does not move in a straight line; homes built 2000 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

2026-10-26T05:44:03.426474 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% 50 70 30 30 60 20 62 50 38 40 100 60 Before 1999 1999 2000 After 2000

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

  • 40% of homes built after 2000 had a price cut before sale, against 50% of homes built before 1999. Defined in 8.1.7.
  • 100% of homes built after 2000 had the seller pay closing costs or repairs, against 70% of homes built before 1999. Defined in 8.1.8.
  • 60% of homes built after 2000 have a view, against 30% of homes built before 1999. 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 199910 sales199910 sales20008 salesAfter 20005 salesAll33 salesReal difference?
Net sale price average$602,158$564,445$589,750$618,996$590,273unclear
Net price per SF average$213$208$218$225$214unclear
Living area average2,8482,7162,6922,7482,755unclear
Year built median19981999200020011999by design

5.10 The numbers: selling

Before 199910 sales199910 sales20008 salesAfter 20005 salesAll33 salesReal difference?
Days on market median3018321425unclear
Discount from original list average5.3%5.8%6.1%4.2%5.5%unclear
Price cut before sale50%30%62%40%45%unclear
Seller paid closing costs or repairs70%60%50%100%67%unclear
Has a view30%20%38%60%33%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 · 33 sales · October 26, 2025 – October 25, 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.

2026-10-26T05:44:03.444603 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 22 33 sales Sales per group View: 11 sales (33%) No view: 22 sales (67%)
Bottom line: no measure differs enough between the groups to rule out chance.

6.1 Key differences

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

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$628K$572Kunclear
Net price per SF$220 per SF$212 per SFunclear
Living area2,853 SF2,706 SFunclear
Year built20001999unclear
Days on market26 days22 daysunclear
Discount from original list5.8%5.3%unclear
Price cut before sale64%36%unclear
Seller paid closing costs or repairs82%59%unclear

6.3 Net sale price: no clear difference

2026-10-26T05:44:03.460669 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 22 sales $0K $200K $400K $600K $628K $572K Net sale price, average

The average is $628K for homes with a view and $572K 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

2026-10-26T05:44:03.478708 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 22 sales $0 $100 $200 $220 $212 Net price per SF, average

The average is $220 per SF for homes with a view and $212 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

2026-10-26T05:44:03.495814 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 22 sales 0 1,000 2,000 3,000 2,853 2,706 Living area (SF), average

The average is 2,853 SF for homes with a view and 2,706 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T05:44:03.539951 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 22 sales 1998 1999 2000 2000 1999 Year built: median (dot) and middle half (bar)

The median is 2000 for homes with a view and 1999 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T05:44:03.557396 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 22 sales 0 10 20 30 26 22 Days on market, median

The median is 26 days for homes with a view and 22 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

2026-10-26T05:44:03.575882 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 22 sales 0.0% 2.0% 4.0% 6.0% 5.8% 5.3% Discount from original list, average

The average is 5.8% for homes with a view and 5.3% 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

2026-10-26T05:44:03.594645 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 64 82 36 59 View No view

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

  • 64% of homes with a view had a price cut before sale, against 36% of homes without a view. Defined in 8.1.7.
  • 82% of homes with a view had the seller pay closing costs or repairs, against 59% 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

View11 salesNo view22 salesAll33 salesReal difference?
Net sale price average$627,550$571,635$590,273unclear
Net price per SF average$220$212$214unclear
Living area average2,8532,7062,755unclear
Year built median200019991999unclear

6.11 The numbers: selling

View11 salesNo view22 salesAll33 salesReal difference?
Days on market median262225unclear
Discount from original list average5.8%5.3%5.5%unclear
Price cut before sale64%36%45%unclear
Seller paid closing costs or repairs82%59%67%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 · October 26, 2025 – October 25, 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 Stone Canyon.

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
33 resale sales. Average $590,273; median $544,497; standard deviation $125,628; middle half (25th–75th percentile) $510,775–$680,000; lowest $378,000, highest $913,820. 22 sales had a seller payment; their median payment was $5,150.

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
33 resale sales. Average $214; median $214; standard deviation $25; middle half (25th–75th percentile) $203–$230; lowest $139, highest $279.

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
33 resale sales. Average 2,755; median 2,714; standard deviation 476; middle half (25th–75th percentile) 2,453–3,065; lowest 1,861, highest 3,844.

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
33 resale sales. Average 1999; median 1999; standard deviation 1; middle half (25th–75th percentile) 1998–2000; lowest 1996, highest 2001.

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
33 resale sales. Average 55; median 25; standard deviation 63; middle half (25th–75th percentile) 7–89; lowest 0, highest 223. 1 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
33 resale sales. Average 5.5%; median 5.4%; standard deviation 6.1%; middle half (25th–75th percentile) 2.7%–7.1%; lowest −9.2%, highest 31.3%. 1 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 33 resale sales (45.5%).

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
22 of 33 resale sales (66.7%).

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
11 sales with a view, 22 without, 0 unclassified. Most common View entries: None 20, Park/Greenbelt 11, Trees/Woods 3, Neighborhood 2, Garden 1, Panoramic 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
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Round Rock, SubdivisionName contains any of “stone canyon” (case-insensitive). A record is kept when its subdivision name belongs to the Stone Canyon family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 33 closed Stone Canyon records over the prior year, in ZIP 78681. 20 subdivision spellings kept, the most common: Stone Canyon Sec 08A (4); Stone Canyon Sec 04 (4); Stone Canyon Sec 01 (3); Stone Canyon Sec 06C (3); Stone Canyon Sec 08-B (2); Stone Canyon Sec 03 (2); Stone Canyon (2); Stone Canyon Sec 4 (1); Stone Canyon Sec 5-A (1); Stone Canyon Sec 7-A (1); STONE CANYON (1); Stone Canyon Sec 7B (1); and 8 more (8 records). No other names were found by the search.

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 17 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
33 single-family sales in the window: 33 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
33 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 $511K”.
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 $511K: $378,000–$510,631 (8 sales); $511K–$531K: $510,775–$530,800 (8 sales); $544K–$680K: $544,497–$680,000 (9 sales); Over $680K: $710,000–$913,820 (8 sales)
Quartiles by living area: Under 2,453 SF: 1,861–2,426 SF (8 sales); 2,453–2,685 SF: 2,453–2,685 SF (8 sales); 2,714–3,065 SF: 2,714–3,065 SF (9 sales); Over 3,065 SF: 3,213–3,844 SF (8 sales)
Quartiles by year built: Before 1999: 1996–1998 (10 sales); 1999: 1999–1999 (10 sales); 2000: 2000–2000 (8 sales); After 2000: 2001–2001 (5 sales)
View and no view: View: MLS lists a view (11 sales); No view: None or Neighborhood (22 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 $590,273, median $544,497. Days on market: average 55, median 25: 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
2 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 = 10.7230.0133p < 0.0063Unclearε² = 0.335large
Living areaKruskal–WallisH = 19.8430.0002p < 0.0063Yesε² = 0.620large
Year builtKruskal–WallisH = 1.3530.7167p < 0.0063Unclearε² = 0.042small
Days on marketKruskal–WallisH = 3.0830.3797p < 0.0063Unclearε² = 0.096medium
Discount from original listKruskal–WallisH = 2.5430.4690p < 0.0063Unclearε² = 0.079medium
Price cut before saleChi-squareχ² = 2.8630.4134p < 0.0063UnclearCramér’s V = 0.294small
Seller paid closing costs or repairsChi-squareχ² = 1.0630.7861p < 0.0063UnclearCramér’s V = 0.179small
Has a viewChi-squareχ² = 1.5030.6823p < 0.0063UnclearCramér’s V = 0.213small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 20.9430.0001p < 0.0063Yesε² = 0.654large
Net price per SFKruskal–WallisH = 1.2130.7510p < 0.0063Unclearε² = 0.038small
Year builtKruskal–WallisH = 2.2330.5267p < 0.0063Unclearε² = 0.070medium
Days on marketKruskal–WallisH = 1.9730.5782p < 0.0063Unclearε² = 0.062medium
Discount from original listKruskal–WallisH = 1.0430.7910p < 0.0063Unclearε² = 0.033small
Price cut before saleChi-squareχ² = 0.3430.9521p < 0.0063UnclearCramér’s V = 0.102small
Seller paid closing costs or repairsChi-squareχ² = 4.8830.1812p < 0.0063UnclearCramér’s V = 0.384medium
Has a viewChi-squareχ² = 3.1230.3728p < 0.0063UnclearCramér’s V = 0.308medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 0.1230.9887p < 0.0063Unclearε² = 0.004negligible
Net price per SFKruskal–WallisH = 2.1930.5338p < 0.0063Unclearε² = 0.068medium
Living areaKruskal–WallisH = 0.8930.8281p < 0.0063Unclearε² = 0.028small
Days on marketKruskal–WallisH = 1.1430.7676p < 0.0063Unclearε² = 0.036small
Discount from original listKruskal–WallisH = 1.1830.7578p < 0.0063Unclearε² = 0.037small
Price cut before saleChi-squareχ² = 2.0430.5633p < 0.0063UnclearCramér’s V = 0.249small
Seller paid closing costs or repairsChi-squareχ² = 3.7530.2898p < 0.0063UnclearCramér’s V = 0.337medium
Has a viewChi-squareχ² = 2.5130.4730p < 0.0063UnclearCramér’s V = 0.276small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 144.00—0.3902p < 0.0063Unclearrank-biserial r = 0.190small
Net price per SFMann–Whitney UU = 131.00—0.7168p < 0.0063Unclearrank-biserial r = 0.083negligible
Living areaMann–Whitney UU = 129.50—0.7599p < 0.0063Unclearrank-biserial r = 0.070negligible
Year builtMann–Whitney UU = 146.50—0.3262p < 0.0063Unclearrank-biserial r = 0.211small
Days on marketMann–Whitney UU = 129.50—0.7599p < 0.0063Unclearrank-biserial r = 0.070negligible
Discount from original listMann–Whitney UU = 144.00—0.3902p < 0.0063Unclearrank-biserial r = 0.190small
Price cut before saleChi-squareχ² = 2.2010.1380p < 0.0063UnclearCramér’s V = 0.258small
Seller paid closing costs or repairsChi-squareχ² = 1.7010.1917p < 0.0063UnclearCramér’s V = 0.227small

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 33 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 October 26, 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.