ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Glenwood Ph-5

Hutto, TX 78634
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 · 5:07 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
23
single-family resale homes
Median net sale price
$276,500
average $277,292
Median net price per SF
$167
average $171
Median days on market
75 days
average 88 days
1. SummaryResale homes · 23 sales · October 26, 2025 – October 25, 2026

This study looks at the 23 resale homes sold in Glenwood Ph-5 in the 365 days to October 25, 2026. A full year is used because only 11 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 sold23 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 $257K · 6 sales$257K–$276K · 6 sales$285K–$294K · 5 salesOver $294K · 6 sales
3. Quartiles by net sale priceResale homes · 23 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.

2026-10-26T05:07:14.536776 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 5 6 23 sales Sales per group Under $257K: 6 sales (26%) $257K–$276K: 6 sales (26%) $285K–$294K: 5 sales (22%) Over $294K: 6 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 $257K$257K–$276K$285K–$294KOver $294K
Higher-priced homes Over $294K
  • Are much larger.
Lower-priced homes Under $257K
  • 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 $257K$257K–$276K$285K–$294KOver $294KReal difference?
Net price per SF$189 per SF$171 per SF$160 per SF$160 per SFunclear
Living area1,265 SFSmallest1,585 SF1,828 SF2,069 SFLargest✓ large
Year built2004201320132016unclear
Days on market30 days108 days47 days72 daysunclear
Discount from original list4.1%9.5%7.3%5.3%unclear
Price cut before sale33%83%60%67%unclear
Seller paid closing costs or repairs83%100%100%67%unclear
Has a view0%17%0%0%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

2026-10-26T05:07:14.565271 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $257K 6 sales $257K– $276K 6 sales $285K– $294K 5 sales Over $294K 6 sales $0 $100 $200 $189 $171 $160 $160 Net price per SF, average

The average is $160 per SF for homes over $294K and $189 per SF for homes under $257K. It falls 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 $294K are about 800 SF (64%) larger than homes under $257K

2026-10-26T05:07:14.587901 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $257K 6 sales $257K– $276K 6 sales $285K– $294K 5 sales Over $294K 6 sales 0 1,000 2,000 1,265 1,585 1,828 2,069 Living area (SF), average

The average is 2,069 SF for homes over $294K and 1,265 SF for homes under $257K. 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

2026-10-26T05:07:14.612051 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $257K 6 sales $257K– $276K 6 sales $285K– $294K 5 sales Over $294K 6 sales 2005 2008 2011 2014 2004 2013 2013 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $294K and 2004 for homes under $257K. 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

2026-10-26T05:07:14.635740 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $257K 6 sales $257K– $276K 6 sales $285K– $294K 5 sales Over $294K 6 sales 0 50 100 30 108 47 72 Days on market, median

The median is 72 days for homes over $294K and 30 days for homes under $257K. It does not move in a straight line; homes $257K–$276K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:07:14.658181 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $257K 6 sales $257K– $276K 6 sales $285K– $294K 5 sales Over $294K 6 sales 0.0% 5.0% 10.0% 4.1% 9.5% 7.3% 5.3% Discount from original list, average

The average is 5.3% for homes over $294K and 4.1% for homes under $257K. It does not move in a straight line; homes $257K–$276K 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

2026-10-26T05:07:14.688320 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% 33 83 0 83 100 17 60 100 0 67 67 0 Under $257K $257K–$276K $285K–$294K Over $294K

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

  • 67% of homes over $294K had a price cut before sale, against 33% of homes under $257K. Defined in 8.1.7.
  • 67% of homes over $294K had the seller pay closing costs or repairs, against 83% of homes under $257K. Defined in 8.1.8.
  • 0% of homes over $294K have a view, against 0% of homes under $257K. 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 $257K6 sales$257K–$276K6 sales$285K–$294K5 salesOver $294K6 salesAll23 salesReal difference?
Net sale price average$234,904$267,512$290,303$318,617$277,292by design
Net price per SF average$189$171$160$160$171unclear
Living area average1,2651,5851,8282,0691,680✓ large
Year built median20042013201320162013unclear

3.10 The numbers: selling

Under $257K6 sales$257K–$276K6 sales$285K–$294K5 salesOver $294K6 salesAll23 salesReal difference?
Days on market median30108477275unclear
Discount from original list average4.1%9.5%7.3%5.3%6.5%unclear
Price cut before sale33%83%60%67%61%unclear
Seller paid closing costs or repairs83%100%100%67%87%unclear
Has a view0%17%0%0%4%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 · 23 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.

2026-10-26T05:07:14.709702 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 5 6 23 sales Sales per group Under 1,478 SF: 6 sales (26%) 1,478–1,562 SF: 6 sales (26%) 1,613–1,911 SF: 5 sales (22%) Over 1,911 SF: 6 sales (26%)
Bottom line

4.1 Key differences

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

Under 1,478 SF1,478–1,562 SF1,613–1,911 SFOver 1,911 SF
Larger homes Over 1,911 SF
  • Sell for less per square foot.
  • Sell for much more.
Smaller homes Under 1,478 SF
  • Sell for more per square foot.
  • 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 1,478 SF1,478–1,562 SF1,613–1,911 SFOver 1,911 SFReal difference?
Net sale price$239KLowest$273K$295K$306KHighest✓ large
Net price per SF$196 per SFHighest$179 per SF$168 per SF$139 per SFLowest✓ large
Year built2006201420142010unclear
Days on market30 days64 days75 days130 daysunclear
Discount from original list3.8%7.3%7.4%7.9%unclear
Price cut before sale33%50%80%83%unclear
Seller paid closing costs or repairs83%100%80%83%unclear
Has a view17%0%0%0%unclear

4.3 Homes over 1,911 SF sell for about $66K (28%) more than homes under 1,478 SF

2026-10-26T05:07:14.730516 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,478 SF 6 sales 1,478– 1,562 SF 6 sales 1,613– 1,911 SF 5 sales Over 1,911 SF 6 sales $0K $100K $200K $300K $239K $273K $295K $306K Net sale price, average

The average is $306K for homes over 1,911 SF and $239K for homes under 1,478 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 1,911 SF sell for about $57 per SF (29%) less than homes under 1,478 SF

2026-10-26T05:07:14.753811 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,478 SF 6 sales 1,478– 1,562 SF 6 sales 1,613– 1,911 SF 5 sales Over 1,911 SF 6 sales $0 $100 $200 $196 $179 $168 $139 Net price per SF, average

The average is $139 per SF for homes over 1,911 SF and $196 per SF for homes under 1,478 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-26T05:07:14.777652 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,478 SF 6 sales 1,478– 1,562 SF 6 sales 1,613– 1,911 SF 5 sales Over 1,911 SF 6 sales 2005 2008 2011 2014 2006 2014 2014 2010 Year built: median (dot) and middle half (bar)

The median is 2010 for homes over 1,911 SF and 2006 for homes under 1,478 SF. It does not move in a straight line; homes 1,478–1,562 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:07:14.800760 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,478 SF 6 sales 1,478– 1,562 SF 6 sales 1,613– 1,911 SF 5 sales Over 1,911 SF 6 sales 0 50 100 150 30 64 75 130 Days on market, median

The median is 130 days for homes over 1,911 SF and 30 days for homes under 1,478 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:07:14.823764 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,478 SF 6 sales 1,478– 1,562 SF 6 sales 1,613– 1,911 SF 5 sales Over 1,911 SF 6 sales 0.0% 2.5% 5.0% 7.5% 3.8% 7.3% 7.4% 7.9% Discount from original list, average

The average is 7.9% for homes over 1,911 SF and 3.8% for homes under 1,478 SF. It rises step by step from the lowest range to the 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

2026-10-26T05:07:14.850892 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% 33 83 17 50 100 0 80 80 0 83 83 0 Under 1,478 SF 1,478–1,562 SF 1,613–1,911 SF Over 1,911 SF

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

  • 83% of homes over 1,911 SF had a price cut before sale, against 33% of homes under 1,478 SF. Defined in 8.1.7.
  • 83% of homes over 1,911 SF had the seller pay closing costs or repairs, against 83% of homes under 1,478 SF. Defined in 8.1.8.
  • 0% of homes over 1,911 SF have a view, against 17% of homes under 1,478 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 1,478 SF6 sales1,478–1,562 SF6 sales1,613–1,911 SF5 salesOver 1,911 SF6 salesAll23 salesReal difference?
Net sale price average$239,150$272,686$294,595$305,619$277,292✓ large
Net price per SF average$196$179$168$139$171✓ large
Living area average1,2351,5201,7612,2191,680by design
Year built median20062014201420102013unclear

4.10 The numbers: selling

Under 1,478 SF6 sales1,478–1,562 SF6 sales1,613–1,911 SF5 salesOver 1,911 SF6 salesAll23 salesReal difference?
Days on market median30647513075unclear
Discount from original list average3.8%7.3%7.4%7.9%6.5%unclear
Price cut before sale33%50%80%83%61%unclear
Seller paid closing costs or repairs83%100%80%83%87%unclear
Has a view17%0%0%0%4%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 · 23 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.

2026-10-26T05:07:14.871733 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 4 6 6 23 sales Sales per group Before 2005: 7 sales (30%) 2005–2012: 4 sales (17%) 2013–2015: 6 sales (26%) After 2015: 6 sales (26%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-10-26T05:07:14.892253 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 7 sales 2005– 2012 4 sales 2013– 2015 6 sales After 2015 6 sales $0K $100K $200K $300K $260K $259K $288K $299K Net sale price, average

The average is $299K for homes built after 2015 and $260K for homes built before 2005. It does not move in a straight line; homes built after 2015 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T05:07:14.915485 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 7 sales 2005– 2012 4 sales 2013– 2015 6 sales After 2015 6 sales $0 $100 $200 $162 $184 $186 $156 Net price per SF, average

The average is $156 per SF for homes built after 2015 and $162 per SF for homes built before 2005. It does not move in a straight line; homes built 2013–2015 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T05:07:14.937230 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 7 sales 2005– 2012 4 sales 2013– 2015 6 sales After 2015 6 sales 0 1,000 2,000 1,631 1,503 1,555 1,981 Living area (SF), average

The average is 1,981 SF for homes built after 2015 and 1,631 SF for homes built before 2005. It does not move in a straight line; homes built after 2015 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T05:07:14.958690 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 7 sales 2005– 2012 4 sales 2013– 2015 6 sales After 2015 6 sales 0 50 100 150 134 26 46 90 Days on market, median

The median is 90 days for homes built after 2015 and 134 days for homes built before 2005. It does not move in a straight line; homes built before 2005 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T05:07:14.982045 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 7 sales 2005– 2012 4 sales 2013– 2015 6 sales After 2015 6 sales 0.0% 5.0% 10.0% 8.7% 1.6% 5.1% 8.7% Discount from original list, average

The average is 8.7% for homes built after 2015 and 8.7% for homes built before 2005. It does not move in a straight line; homes built after 2015 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T05:07:15.007391 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% 71 100 0 25 50 25 50 83 0 83 100 0 Before 2005 2005–2012 2013–2015 After 2015

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

  • 83% of homes built after 2015 had a price cut before sale, against 71% of homes built before 2005. Defined in 8.1.7.
  • 100% of homes built after 2015 had the seller pay closing costs or repairs, against 100% of homes built before 2005. Defined in 8.1.8.
  • 0% of homes built after 2015 have a view, against 0% of homes built before 2005. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 20057 sales2005–20124 sales2013–20156 salesAfter 20156 salesAll23 sales
Net sale price average$259,534$259,225$288,013$299,332$277,292
Net price per SF average$162$184$186$156$171
Living area average1,6311,5031,5551,9811,680
Year built median20042006201420162013

5.10 The numbers: selling

Before 20057 sales2005–20124 sales2013–20156 salesAfter 20156 salesAll23 sales
Days on market median13426469075
Discount from original list average8.7%1.6%5.1%8.7%6.5%
Price cut before sale71%25%50%83%61%
Seller paid closing costs or repairs100%50%83%100%87%
Has a view0%25%0%0%4%

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 · 23 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T05:07:15.026350 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 1 21 22 sales Sales per group View: 1 sales (5%) No view: 21 sales (95%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T05:07:15.042207 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 21 sales $0K $100K $200K $300K $276K $275K Net sale price, average

The average is $276K for homes with a view and $275K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T05:07:15.061078 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 21 sales $0 $50 $100 $150 $200 $200 $170 Net price per SF, average

The average is $200 per SF for homes with a view and $170 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T05:07:15.081294 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 21 sales 0 500 1,000 1,500 2,000 1,382 1,673 Living area (SF), average

The average is 1,382 SF for homes with a view and 1,673 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T05:07:15.129689 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 21 sales 2005 2008 2011 2014 2012 2013 Year built: median (dot) and middle half (bar)

The median is 2012 for homes with a view and 2013 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T05:07:15.148590 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 21 sales 0 20 40 60 80 75 69 Days on market, median

The median is 75 days for homes with a view and 69 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T05:07:15.167378 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 21 sales 0.0% 2.0% 4.0% 6.0% 6.3% 6.4% Discount from original list, average

The average is 6.3% for homes with a view and 6.4% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T05:07:15.186645 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 0 100 62 86 View No view

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

  • 0% of homes with a view had a price cut before sale, against 62% of homes without a view. Defined in 8.1.7.
  • 100% of homes with a view had the seller pay closing costs or repairs, against 86% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View1 salesNo view21 salesAll22 sales
Net sale price average$276,500$274,748$274,828
Net price per SF average$200$170$171
Living area average1,3821,6731,660
Year built median201220132012

6.11 The numbers: selling

View1 salesNo view21 salesAll22 sales
Days on market median756972
Discount from original list average6.3%6.4%6.3%
Price cut before sale0%62%59%
Seller paid closing costs or repairs100%86%86%

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 Glenwood Ph-5.

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
23 resale sales. Average $277,292; median $276,500; standard deviation $35,626; middle half (25th–75th percentile) $255,496–$293,808; lowest $195,000, highest $349,000. 20 sales had a seller payment; their median payment was $8,500.

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
23 resale sales. Average $171; median $167; standard deviation $30; middle half (25th–75th percentile) $151–$192; lowest $120, highest $253.

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
23 resale sales. Average 1,680; median 1,562; standard deviation 422; middle half (25th–75th percentile) 1,430–1,946; lowest 1,006, highest 2,902.

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
23 resale sales. Average 2010; median 2013; standard deviation 6; middle half (25th–75th percentile) 2004–2016; lowest 2003, highest 2016.

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
23 resale sales. Average 88; median 75; standard deviation 78; middle half (25th–75th percentile) 21–110; lowest 6, highest 285. 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
23 resale sales. Average 6.5%; median 7.4%; standard deviation 4.9%; middle half (25th–75th percentile) 2.9%–9.9%; lowest −5.4%, highest 14.5%. 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
14 of 23 resale sales (60.9%).

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 23 resale sales (87.0%).

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
1 sales with a view, 21 without, 1 unclassified. Most common View entries: None 16, Neighborhood 5, Pasture 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 = Hutto, SubdivisionName contains any of “glenwood ph 5”, “glenwood”, “glenwood ph-5” (case-insensitive). A record is kept when its subdivision name belongs to the Glenwood Ph-5 family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 23 closed Glenwood Ph-5 records over the prior year, in ZIP 78634. 12 subdivision spellings kept: Glenwood Ph 01 (8); Glenwood (3); Glenwood Ph 04B (2); Glenwood Ph 5 (2); Glenwood Ph 02B (1); Glenwood Ph-5 (1); Glenwood Ph 3B Sec 50 A (1); Glenwood Ph 6B (1); Glenwood Ph 3A (1); GLENWOOD PH 6B (1); GLENWOOD (1); Glenwood Ph 3a (1). 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 11 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
23 single-family sales in the window: 23 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
23 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 $257K”.
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 $257K: $195,000–$254,400 (6 sales); $257K–$276K: $256,593–$276,500 (6 sales); $285K–$294K: $285,000–$293,715 (5 sales); Over $294K: $293,900–$349,000 (6 sales)
Quartiles by living area: Under 1,478 SF: 1,006–1,382 SF (6 sales); 1,478–1,562 SF: 1,478–1,562 SF (6 sales); 1,613–1,911 SF: 1,613–1,911 SF (5 sales); Over 1,911 SF: 1,981–2,902 SF (6 sales)
Quartiles by year built: Before 2005: 2003–2004 (7 sales); 2005–2012: 2005–2012 (4 sales); 2013–2015: 2013–2015 (6 sales); After 2015: 2016–2016 (6 sales)
View and no view: View: MLS lists a view (1 sales); No view: None or Neighborhood (21 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 $277,292, median $276,500. Days on market: average 88, median 75: 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

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
3 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 = 3.4030.3345p < 0.0063Unclearε² = 0.154large
Living areaKruskal–WallisH = 12.8830.0049p < 0.0063Yesε² = 0.586large
Year builtKruskal–WallisH = 7.0830.0695p < 0.0063Unclearε² = 0.322large
Days on marketKruskal–WallisH = 3.2430.3566p < 0.0063Unclearε² = 0.147large
Discount from original listKruskal–WallisH = 3.5130.3199p < 0.0063Unclearε² = 0.159large
Price cut before saleChi-squareχ² = 3.2730.3522p < 0.0063UnclearCramér’s V = 0.377medium
Seller paid closing costs or repairsChi-squareχ² = 3.9030.2728p < 0.0063UnclearCramér’s V = 0.412medium
Has a viewChi-squareχ² = 2.9630.3975p < 0.0063UnclearCramér’s V = 0.359medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 12.5530.0057p < 0.0063Yesε² = 0.570large
Net price per SFKruskal–WallisH = 12.9930.0047p < 0.0063Yesε² = 0.590large
Year builtKruskal–WallisH = 2.6530.4491p < 0.0063Unclearε² = 0.120medium
Days on marketKruskal–WallisH = 5.1430.1619p < 0.0063Unclearε² = 0.234large
Discount from original listKruskal–WallisH = 1.7830.6194p < 0.0063Unclearε² = 0.081medium
Price cut before saleChi-squareχ² = 4.2530.2360p < 0.0063UnclearCramér’s V = 0.430medium
Seller paid closing costs or repairsChi-squareχ² = 1.2530.7405p < 0.0063UnclearCramér’s V = 0.233small
Has a viewChi-squareχ² = 2.9630.3975p < 0.0063UnclearCramér’s V = 0.359medium

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

Too few sales in a group to test.

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 23 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.