• Re: OT: Consequences

    From Tom Elam@[email protected] to comp.sys.mac.advocacy on Mon Nov 3 17:31:00 2025
    From Newsgroup: comp.sys.mac.advocacy

    On 10/30/2025 6:24 AM, -hh wrote:
    On 10/29/25 11:22, Tom Elam wrote:
    On 10/28/2025 1:15 PM, Alan wrote:
    On 2025-10-28 03:06, -hh wrote:
    On 10/27/25 08:08, Tom Elam wrote:
    In the past both Alan Baker has stated that Vancouver BC high
    housing prices are an indication of high housing demand because
    it's an attractive place to live...
    My home state of Indiana?

    Gosh golly:  comparing a city to State.

    Care to tell us what State has a higher homeless rate than its major
    cities?

    Does the asshole care to tell us what the overnight low temperatures
    are during winters in Indiana vs those in Vancouver?



    Why this post? Just to piss off Alan.

    What it really does is show that you're a butthurt troll luzer.


    But there IS substance here too.

    U.S. source

    https://nlihc.org/sites/default/files/Causes-and-Solutions-to-
    Homelessness.pdf

    "The primary solution to homelessness...

    Wrong question.


    Canadian source:

    "A critical shortage of housing that is affordable, safe and stable
    directly contributes to homelessness...

    Again, wrong question.


    Blaming climate is at best a deflection, at worst an outright lie.
    Nowhere in either source is weather mentioned.

    Try searching on the point being raised, instead of your agenda:

    "is climate a factor in where homeless people congregate?"

    "Abstract

    It is widely understood that climate affects the spatial distribution of homelessness—warm places have on average higher rates of unsheltered homelessness than cold places."

    "Conventional wisdom among local officials and experts in cities with
    warm climates is that warm temperatures are major draws for homeless individuals.[1]

    Similarly, research has generally affirmed that homelessness, and particularly the unsheltered type, is more common in warmer areas."

    <https://www.sciencedirect.com/science/article/abs/pii/S1051137717302231>

    "On the Relationship Between Climate and Homelessness

    Abstract

    It is well understood that unsheltered homelessness is on average more common in communities with warmer climates. In this paper, we show that
    cold places uniformly have low rates of unsheltered homelessness, while
    warm places display wide variation."

    <https://www.aei.org/wp-content/uploads/2017/03/homelessness-climate- update.pdf>


    Since your career was as a consultant that required research, your unwillingness to acknowledge this factor speaks volumes:

    have you had significant cognitive decline to have missed such an clear association?

    Or were you never really good at your job?

    Or worse yet, did you know better anyway, as you you were only being
    hired because you'd deliver the conclusion that the customer wanted,
    even if it wasn't truthful?

    "Choose your poison."


    -hh

    Correlation is not causation. Halley's Comet was closest to the Earth
    the day Samuel Langhorne Clemens was born and the day he died. Was he a
    child of the comet? Thomas Jefferson and John Adams both died on July 4,
    1826. Did the 50th anniversary of the Declaration of Independence kill
    them both?

    I am a keen student of cause and effect. You apparently are not.

    So why is housing generally less affordable on the coasts and in
    moderate climates.

    Searched "Causes of Homelessness in America". None mentioned weather.
    Housing is less affordable in places that are attractive to live. You
    are the one who is guilty of looking for confirmation.

    Homelessness is multifaceted. However, every one of these citations
    below state that housing affordability is the #1 driver of homelessness.
    It's no accident that homelessness is significantly higher in a city
    where a 500 square foot condo has a market value that is the same as
    2500 square foot home in the U.S. Midwest.

    https://publichealth.jhu.edu/2025/we-can-end-homelessness-in-america

    https://www.pew.org/en/research-and-analysis/articles/2023/08/22/how-housing-costs-drive-levels-of-homelessness

    https://endpovertynowinc.org/blog/10-causes-of-homelessness-in-america/

    https://endhomelessness.org/overview/

    https://nlihc.org/sites/default/files/Causes-and-Solutions-to-Homelessness.pdf

    https://homelesslaw.org/wp-content/uploads/2018/10/Homeless_Stats_Fact_Sheet.pdf

    https://www.aclu.org/documents/fact-sheet-state-of-homelessness-in-the-us


    --- Synchronet 3.21a-Linux NewsLink 1.2
  • From Tom Elam@[email protected] to comp.sys.mac.advocacy on Mon Nov 3 18:12:27 2025
    From Newsgroup: comp.sys.mac.advocacy

    On 10/30/2025 6:24 AM, -hh wrote:
    On 10/29/25 11:22, Tom Elam wrote:
    On 10/28/2025 1:15 PM, Alan wrote:
    On 2025-10-28 03:06, -hh wrote:
    On 10/27/25 08:08, Tom Elam wrote:
    In the past both Alan Baker has stated that Vancouver BC high
    housing prices are an indication of high housing demand because
    it's an attractive place to live...
    My home state of Indiana?

    Gosh golly:  comparing a city to State.

    Care to tell us what State has a higher homeless rate than its major
    cities?

    Does the asshole care to tell us what the overnight low temperatures
    are during winters in Indiana vs those in Vancouver?



    Why this post? Just to piss off Alan.

    What it really does is show that you're a butthurt troll luzer.


    But there IS substance here too.

    U.S. source

    https://nlihc.org/sites/default/files/Causes-and-Solutions-to-
    Homelessness.pdf

    "The primary solution to homelessness...

    Wrong question.


    Canadian source:

    "A critical shortage of housing that is affordable, safe and stable
    directly contributes to homelessness...

    Again, wrong question.


    Blaming climate is at best a deflection, at worst an outright lie.
    Nowhere in either source is weather mentioned.

    Try searching on the point being raised, instead of your agenda:

    "is climate a factor in where homeless people congregate?"

    "Abstract

    It is widely understood that climate affects the spatial distribution of homelessness—warm places have on average higher rates of unsheltered homelessness than cold places."

    "Conventional wisdom among local officials and experts in cities with
    warm climates is that warm temperatures are major draws for homeless individuals.[1]

    Similarly, research has generally affirmed that homelessness, and particularly the unsheltered type, is more common in warmer areas."

    <https://www.sciencedirect.com/science/article/abs/pii/S1051137717302231>

    "On the Relationship Between Climate and Homelessness

    Abstract

    It is well understood that unsheltered homelessness is on average more common in communities with warmer climates. In this paper, we show that
    cold places uniformly have low rates of unsheltered homelessness, while
    warm places display wide variation."

    <https://www.aei.org/wp-content/uploads/2017/03/homelessness-climate- update.pdf>


    Since your career was as a consultant that required research, your unwillingness to acknowledge this factor speaks volumes:

    have you had significant cognitive decline to have missed such an clear association?

    Or were you never really good at your job?

    Or worse yet, did you know better anyway, as you you were only being
    hired because you'd deliver the conclusion that the customer wanted,
    even if it wasn't truthful?

    "Choose your poison."


    -hh

    So explain how Mississippi has the lowest homeless rate of 33 per
    100,000 in the country while cold Indiana is about 3x that rate.

    https://www.wjtv.com/news/state/mississippi-has-lowest-rate-of-homelessness-in-us/

    Alabama comes in at under 100 per 100,000.

    https://www.al.com/news/2025/09/10-states-with-the-highest-homeless-population-where-does-alabama-rank.html

    Florida? About 140 per 100,000 and declining.

    https://flhousing.org/wp-content/uploads/2024/06/FHC-Journal-Summer-2024-HUD-Homeless-Report.pdf

    Vancouver City, one of the most expensive housing market in the world? 395/100,000. Much higher than these warm states you postulate should
    have even higher homeless rates than Vancouver since the homeless don't
    need to worry about freezing to death.




    --- Synchronet 3.21a-Linux NewsLink 1.2
  • From Brock McNuggets@[email protected] to comp.sys.mac.advocacy on Tue Nov 4 00:06:12 2025
    From Newsgroup: comp.sys.mac.advocacy

    On Nov 3, 2025 at 4:12:27 PM MST, "Tom Elam" wrote <10ebcsp$37pld$[email protected]>:

    On 10/30/2025 6:24 AM, -hh wrote:

    ...

    Or were you never really good at your job?

    Or worse yet, did you know better anyway, as you you were only being
    hired because you'd deliver the conclusion that the customer wanted,
    even if it wasn't truthful?

    "Choose your poison."


    -hh

    So explain how Mississippi has the lowest homeless rate of 33 per
    100,000 in the country while cold Indiana is about 3x that rate.

    Mississippi puts little effort into counting their homeless, and few shelters and the like to help with that count. They do also have very low housing costs compared to many states.

    But Mississippi also has the highest poverty rates, one of the lowest median household income, highest rates of obesity and diabetes and infant mortality, is near the bottom ranking in education, and the social services and mental health services are more limited than most states.
    --
    It's impossible for someone who is at war with themselves to be at peace with you.
    --- Synchronet 3.21a-Linux NewsLink 1.2
  • From Brock McNuggets@[email protected] to comp.sys.mac.advocacy on Tue Nov 4 00:09:22 2025
    From Newsgroup: comp.sys.mac.advocacy

    On Nov 3, 2025 at 3:31:00 PM MST, "Tom Elam" wrote <10ebaf2$36sdu$[email protected]>:

    On 10/30/2025 6:24 AM, -hh wrote:

    ...


    Since your career was as a consultant that required research, your
    unwillingness to acknowledge this factor speaks volumes:

    have you had significant cognitive decline to have missed such an clear
    association?

    Or were you never really good at your job?

    Or worse yet, did you know better anyway, as you you were only being
    hired because you'd deliver the conclusion that the customer wanted,
    even if it wasn't truthful?

    "Choose your poison."


    -hh

    Correlation is not causation.

    True.

    Halley's Comet was closest to the Earth
    the day Samuel Langhorne Clemens was born and the day he died. Was he a
    child of the comet?

    Likely.

    Thomas Jefferson and John Adams both died on July 4,
    1826. Did the 50th anniversary of the Declaration of Independence kill
    them both?

    Clearly!

    I am a keen student of cause and effect. You apparently are not.

    So why is housing generally less affordable on the coasts and in
    moderate climates.

    Supply and demand.

    Searched "Causes of Homelessness in America". None mentioned weather.
    Housing is less affordable in places that are attractive to live. You
    are the one who is guilty of looking for confirmation.

    Homelessness is multifaceted. However, every one of these citations
    below state that housing affordability is the #1 driver of homelessness.

    Housing prices, income levels, mental illness / support for it, climate (some states it is more apparent because people cannot easily live outside), social safety nets, etc.

    It's no accident that homelessness is significantly higher in a city
    where a 500 square foot condo has a market value that is the same as
    2500 square foot home in the U.S. Midwest.

    https://publichealth.jhu.edu/2025/we-can-end-homelessness-in-america

    https://www.pew.org/en/research-and-analysis/articles/2023/08/22/how-housing-costs-drive-levels-of-homelessness

    https://endpovertynowinc.org/blog/10-causes-of-homelessness-in-america/

    https://endhomelessness.org/overview/

    https://nlihc.org/sites/default/files/Causes-and-Solutions-to-Homelessness.pdf

    https://homelesslaw.org/wp-content/uploads/2018/10/Homeless_Stats_Fact_Sheet.pdf

    https://www.aclu.org/documents/fact-sheet-state-of-homelessness-in-the-us
    --
    It's impossible for someone who is at war with themselves to be at peace with you.
    --- Synchronet 3.21a-Linux NewsLink 1.2
  • From Tom Elam@[email protected] to comp.sys.mac.advocacy on Tue Nov 4 14:45:35 2025
    From Newsgroup: comp.sys.mac.advocacy

    On 10/30/2025 6:24 AM, -hh wrote:
    On 10/29/25 11:22, Tom Elam wrote:
    On 10/28/2025 1:15 PM, Alan wrote:
    On 2025-10-28 03:06, -hh wrote:
    On 10/27/25 08:08, Tom Elam wrote:
    In the past both Alan Baker has stated that Vancouver BC high
    housing prices are an indication of high housing demand because
    it's an attractive place to live...
    My home state of Indiana?

    Gosh golly:  comparing a city to State.

    Care to tell us what State has a higher homeless rate than its major
    cities?

    Does the asshole care to tell us what the overnight low temperatures
    are during winters in Indiana vs those in Vancouver?



    Why this post? Just to piss off Alan.

    What it really does is show that you're a butthurt troll luzer.


    But there IS substance here too.

    U.S. source

    https://nlihc.org/sites/default/files/Causes-and-Solutions-to-
    Homelessness.pdf

    "The primary solution to homelessness...

    Wrong question.


    Canadian source:

    "A critical shortage of housing that is affordable, safe and stable
    directly contributes to homelessness...

    Again, wrong question.


    Blaming climate is at best a deflection, at worst an outright lie.
    Nowhere in either source is weather mentioned.

    Try searching on the point being raised, instead of your agenda:

    "is climate a factor in where homeless people congregate?"

    "Abstract

    It is widely understood that climate affects the spatial distribution of homelessness—warm places have on average higher rates of unsheltered homelessness than cold places."

    "Conventional wisdom among local officials and experts in cities with
    warm climates is that warm temperatures are major draws for homeless individuals.[1]

    Similarly, research has generally affirmed that homelessness, and particularly the unsheltered type, is more common in warmer areas."

    <https://www.sciencedirect.com/science/article/abs/pii/S1051137717302231>

    "On the Relationship Between Climate and Homelessness

    Abstract

    It is well understood that unsheltered homelessness is on average more common in communities with warmer climates. In this paper, we show that
    cold places uniformly have low rates of unsheltered homelessness, while
    warm places display wide variation."

    <https://www.aei.org/wp-content/uploads/2017/03/homelessness-climate- update.pdf>


    Since your career was as a consultant that required research, your unwillingness to acknowledge this factor speaks volumes:

    have you had significant cognitive decline to have missed such an clear association?

    Or were you never really good at your job?

    Or worse yet, did you know better anyway, as you you were only being
    hired because you'd deliver the conclusion that the customer wanted,
    even if it wasn't truthful?

    "Choose your poison."


    -hh

    Now you are depending on narrowing the scope to sheltered versus
    unsheltered, a different argument and a goalpost shift. But your
    argument falls totally apart when you look across the entire U.S.
    Weather is far from a consistent variable in explaining total homeless rates/capita.

    I never said weather cannot ever be a factor. I looked at total
    homelessness in my original post. How do you explain dramatically lower
    TOTAL homeless rates across the southern states from Florida to Arizona
    than is the case in California Oregon, Washington, Nevada, Maine,
    Vermont and New York? Mississippi, with low household income and a nice
    warm climate, at 3.3, has the lowest rate/10,000 in the country. Why?
    Could housing affordability be an important independent variable?

    Your argument that weather is a consistent factor in total homeless rate across the country falls apart.

    HUD 2023 study's rates:

    https://drive.google.com/file/d/1DZSv2KUfCej2T10Md6_ZjA0Wx-50CN2c/view?usp=sharing


    Subject shift----

    This is an example of stats the work I did for my clients.

    So you think you know stats? Here is a problem for you. I have been
    tracking my electric use in this total electric home since 2010. Just
    for fun I built a regression model. It explains 96.5% of the variation
    in monthly average kWh per day billed.

    On October 1, 2024 we replaced our heat pump. I want to know if it made
    a difference in power use. The company that sold it to us claimed it
    would, but power savings were not the primary reason for the replacement.

    First, here are few facts:

    Use depends on weather, temperature to be precise, but is not linear.
    Why is it not linear?

    A graph of local temps and kWh/day:

    https://drive.google.com/file/d/1qSiDqfp_ldcEDeovUIdkhHAV8JwsKafZ/view?usp=sharing

    How would you specify the functional form? Linear (Y = a + bX) will not
    work nearly as well as other functional forms. The linear R^2 is only 71%.

    How would you correct for increasing variance (heteroskedasticity) as temperature falls? Why is this important?

    Why do you think there are 4 major outliers?

    What other factors would you look for other than temperature? Hint, a
    much better nonlinear functional form using only temperature explains
    only 87% of dependent variable variation, about 10 points short with
    other independent variables included.

    How would you determine if the new heat pump is more efficient or not at
    the 95% confidence level?

    Thanks to a new smart thermostat installed with the new heat pump I also
    now have monthly heat pump run time data from last October to date. How
    would you specify a regression between run time and kWh billed? Think
    it's linear or not? What interesting result might you see?

    I await your answers. Functional form is the easiest, but not obvious.

    When you respond I'll share the actual equations based on 1/1/2010 to date.


    --- Synchronet 3.21a-Linux NewsLink 1.2
  • From Tom Elam@[email protected] to comp.sys.mac.advocacy on Tue Nov 4 15:04:26 2025
    From Newsgroup: comp.sys.mac.advocacy

    On 11/3/2025 7:06 PM, Brock McNuggets wrote:
    On Nov 3, 2025 at 4:12:27 PM MST, "Tom Elam" wrote <10ebcsp$37pld$[email protected]>:

    On 10/30/2025 6:24 AM, -hh wrote:

    ...

    Or were you never really good at your job?

    Or worse yet, did you know better anyway, as you you were only being
    hired because you'd deliver the conclusion that the customer wanted,
    even if it wasn't truthful?

    "Choose your poison."


    -hh

    So explain how Mississippi has the lowest homeless rate of 33 per
    100,000 in the country while cold Indiana is about 3x that rate.

    Mississippi puts little effort into counting their homeless, and few shelters and the like to help with that count. They do also have very low housing costs
    compared to many states.

    But Mississippi also has the highest poverty rates, one of the lowest median household income, highest rates of obesity and diabetes and infant mortality, is near the bottom ranking in education, and the social services and mental health services are more limited than most states.


    It's a multifaceted issue with no easy solution. Texas also had a very
    low homeless rate, but much better off than Mississippi. Also much more
    urban.

    I grew up just north of the Tennessee/Mississippi border. When
    comparisons were made our mantra as "Thank God for Mississippi!"
    --- Synchronet 3.21a-Linux NewsLink 1.2
  • From Brock McNuggets@[email protected] to comp.sys.mac.advocacy on Tue Nov 4 20:37:05 2025
    From Newsgroup: comp.sys.mac.advocacy

    On Nov 4, 2025 at 1:04:26 PM MST, "Tom Elam" wrote <10edm87$3rh4t$[email protected]>:

    On 11/3/2025 7:06 PM, Brock McNuggets wrote:
    On Nov 3, 2025 at 4:12:27 PM MST, "Tom Elam" wrote
    <10ebcsp$37pld$[email protected]>:

    On 10/30/2025 6:24 AM, -hh wrote:

    ...

    Or were you never really good at your job?

    Or worse yet, did you know better anyway, as you you were only being
    hired because you'd deliver the conclusion that the customer wanted,
    even if it wasn't truthful?

    "Choose your poison."


    -hh

    So explain how Mississippi has the lowest homeless rate of 33 per
    100,000 in the country while cold Indiana is about 3x that rate.

    Mississippi puts little effort into counting their homeless, and few shelters
    and the like to help with that count. They do also have very low housing costs
    compared to many states.

    But Mississippi also has the highest poverty rates, one of the lowest median >> household income, highest rates of obesity and diabetes and infant mortality,
    is near the bottom ranking in education, and the social services and mental >> health services are more limited than most states.


    It's a multifaceted issue with no easy solution.

    Agreed. But hard for Mississippi to go for bragging rights in how they handle their challenges with poverty.

    Texas also had a very
    low homeless rate, but much better off than Mississippi. Also much more urban.

    I grew up just north of the Tennessee/Mississippi border. When
    comparisons were made our mantra as "Thank God for Mississippi!"

    :) Can see why.
    --
    It's impossible for someone who is at war with themselves to be at peace with you.
    --- Synchronet 3.21a-Linux NewsLink 1.2
  • From -hh@[email protected] to comp.sys.mac.advocacy on Tue Nov 4 16:12:51 2025
    From Newsgroup: comp.sys.mac.advocacy

    On 11/4/25 14:45, Tom Elam wrote:
    On 10/30/2025 6:24 AM, -hh wrote:
    On 10/29/25 11:22, Tom Elam wrote:
    On 10/28/2025 1:15 PM, Alan wrote:
    On 2025-10-28 03:06, -hh wrote:
    On 10/27/25 08:08, Tom Elam wrote:
    In the past both Alan Baker has stated that Vancouver BC high
    housing prices are an indication of high housing demand because
    it's an attractive place to live...
    My home state of Indiana?

    Gosh golly:  comparing a city to State.

    Care to tell us what State has a higher homeless rate than its
    major cities?

    Does the asshole care to tell us what the overnight low temperatures
    are during winters in Indiana vs those in Vancouver?



    Why this post? Just to piss off Alan.

    What it really does is show that you're a butthurt troll luzer.


    But there IS substance here too.

    U.S. source

    https://nlihc.org/sites/default/files/Causes-and-Solutions-to-
    Homelessness.pdf

    "The primary solution to homelessness...

    Wrong question.


    Canadian source:

    "A critical shortage of housing that is affordable, safe and stable
    directly contributes to homelessness...

    Again, wrong question.


    Blaming climate is at best a deflection, at worst an outright lie.
    Nowhere in either source is weather mentioned.

    Try searching on the point being raised, instead of your agenda:

    "is climate a factor in where homeless people congregate?"

    "Abstract

    It is widely understood that climate affects the spatial distribution
    of homelessness—warm places have on average higher rates of
    unsheltered homelessness than cold places."

    "Conventional wisdom among local officials and experts in cities with
    warm climates is that warm temperatures are major draws for homeless
    individuals.[1]

    Similarly, research has generally affirmed that homelessness, and
    particularly the unsheltered type, is more common in warmer areas."

    <https://www.sciencedirect.com/science/article/abs/pii/S1051137717302231>

    "On the Relationship Between Climate and Homelessness

    Abstract

    It is well understood that unsheltered homelessness is on average more
    common in communities with warmer climates. In this paper, we show
    that cold places uniformly have low rates of unsheltered homelessness,
    while warm places display wide variation."

    <https://www.aei.org/wp-content/uploads/2017/03/homelessness-climate-
    update.pdf>


    Since your career was as a consultant that required research, your
    unwillingness to acknowledge this factor speaks volumes:

    have you had significant cognitive decline to have missed such an
    clear association?

    Or were you never really good at your job?

    Or worse yet, did you know better anyway, as you you were only being
    hired because you'd deliver the conclusion that the customer wanted,
    even if it wasn't truthful?

    "Choose your poison."


    -hh

    Now you are depending on narrowing the scope to sheltered versus unsheltered, a different argument and a goalpost shift. But your
    argument falls totally apart when you look across the entire U.S.
    Weather is far from a consistent variable in explaining total homeless rates/capita.

    Nope.


    I never said weather cannot ever be a factor.


    You implied it by focusing only on housing costs.

    I looked at total
    homelessness in my original post. How do you explain dramatically lower TOTAL homeless rates across the southern states from Florida to Arizona
    than is the case in California Oregon, Washington, Nevada, Maine,
    Vermont and New York? Mississippi, with low household income and a nice
    warm climate, at 3.3, has the lowest rate/10,000 in the country. Why?
    Could housing affordability be an important independent variable?

    Sounds like you didn't even bother to read the cite I provided.


    Your argument that weather is a consistent factor in total homeless rate across the country falls apart.

    Fortunately, I wasn't claiming that it is a *consistent* factor, merely
    that it was a factor. As per my cite, one can see that it is consistent within certain contexts though.


    So you think you know stats?

    Don't need to make that personal claim to note where another person's
    alleged numbers go sideways.

    Here is a problem for you. I have been
    tracking my electric use in this total electric home since 2010. Just
    for fun I built a regression model. It explains 96.5% of the variation
    in monthly average kWh per day billed.

    On October 1, 2024 we replaced our heat pump. I want to know if it made
    a difference in power use. The company that sold it to us claimed it
    would, but power savings were not the primary reason for the replacement.

    First, here are few facts:

    Use depends on weather, temperature to be precise, but is not linear.
    Why is it not linear?

    For a variety of factors besides just temperature, which you're trying
    to pretend you actually know. Offhand, I can think of at least three,
    which I've happened to have noticed in my own bill without charts, which indicates they're not significantly lower-order variables.
    A graph of local temps and kWh/day:

    https://drive.google.com/file/d/1qSiDqfp_ldcEDeovUIdkhHAV8JwsKafZ/view? usp=sharing

    How would you specify the functional form? Linear (Y = a + bX) will not
    work nearly as well as other functional forms. The linear R^2 is only 71%.
    Well, I'd not pick linear, as the upward curve on the right is increased demand from air conditioning.
    How would you correct for increasing variance (heteroskedasticity) as temperature falls? Why is this important?

    By not using a univariant model.
    Why do you think there are 4 major outliers?
    What actual proof do you have that there's four?

    My eyeball sees two likely ones, probably one more, but one needs to run
    a formal test with criteria to correctly assess this. Plus after one
    accounts for both first & second order factors (& known nonlinearities),
    there very well may be zero outliers actually present.


    What other factors would you look for other than temperature? Hint, a
    much better nonlinear functional form using only temperature explains
    only 87% of dependent variable variation, about 10 points short with
    other independent variables included.

    As I said, I have some factors that on a first principles standpoint
    must be variance contributors to your model. It seems that you've not
    figured them out and are trolling for free assistance, because you're
    only thinking in two dimensional space instead of more (eg, multivariate).


    How would you determine if the new heat pump is more efficient or not at
    the 95% confidence level?

    With your present data, I wouldn't bother: it has too much noise from
    ~second order variables that you've failed to control for. One doesn't
    bother with the likes of a Student t until the data's clean enough to be useful. So the first real step would be to build a better model on the
    legacy data to replace your trash. FYI, the t was from William Gosset,
    as he was working for Guinness & couldn't publish under his own name.


    Thanks to a new smart thermostat installed with the new heat pump I also
    now have monthly heat pump run time data from last October to date. How would you specify a regression between run time and kWh billed? Think
    it's linear or not? What interesting result might you see?

    Since you're ignoring several contributing variables (hence your high variance), what you'll have will be noisy & uninteresting trash.


    I await your answers. Functional form is the easiest, but not obvious.

    When you respond I'll share the actual equations based on 1/1/2010 to date.

    At which point I may note for myself what variables you've ignored, and
    which I may or may not bother to post...you going to pay my consulting fee?

    -hh
    --- Synchronet 3.21a-Linux NewsLink 1.2
  • From Tom Elam@[email protected] to comp.sys.mac.advocacy on Fri Nov 7 17:32:31 2025
    From Newsgroup: comp.sys.mac.advocacy

    On 11/4/2025 4:12 PM, -hh wrote:
    On 11/4/25 14:45, Tom Elam wrote:
    On 10/30/2025 6:24 AM, -hh wrote:
    On 10/29/25 11:22, Tom Elam wrote:
    On 10/28/2025 1:15 PM, Alan wrote:
    On 2025-10-28 03:06, -hh wrote:
    On 10/27/25 08:08, Tom Elam wrote:
    In the past both Alan Baker has stated that Vancouver BC high
    housing prices are an indication of high housing demand because >>>>>>> it's an attractive place to live...
    My home state of Indiana?

    Gosh golly:  comparing a city to State.

    Care to tell us what State has a higher homeless rate than its
    major cities?

    Does the asshole care to tell us what the overnight low
    temperatures are during winters in Indiana vs those in Vancouver?



    Why this post? Just to piss off Alan.

    What it really does is show that you're a butthurt troll luzer.


    But there IS substance here too.

    U.S. source

    https://nlihc.org/sites/default/files/Causes-and-Solutions-to-
    Homelessness.pdf

    "The primary solution to homelessness...

    Wrong question.


    Canadian source:

    "A critical shortage of housing that is affordable, safe and stable
    directly contributes to homelessness...

    Again, wrong question.


    Blaming climate is at best a deflection, at worst an outright lie.
    Nowhere in either source is weather mentioned.

    Try searching on the point being raised, instead of your agenda:

    "is climate a factor in where homeless people congregate?"

    "Abstract

    It is widely understood that climate affects the spatial distribution
    of homelessness—warm places have on average higher rates of
    unsheltered homelessness than cold places."

    "Conventional wisdom among local officials and experts in cities with
    warm climates is that warm temperatures are major draws for homeless
    individuals.[1]

    Similarly, research has generally affirmed that homelessness, and
    particularly the unsheltered type, is more common in warmer areas."

    <https://www.sciencedirect.com/science/article/abs/pii/
    S1051137717302231>

    "On the Relationship Between Climate and Homelessness

    Abstract

    It is well understood that unsheltered homelessness is on average
    more common in communities with warmer climates. In this paper, we
    show that cold places uniformly have low rates of unsheltered
    homelessness, while warm places display wide variation."

    <https://www.aei.org/wp-content/uploads/2017/03/homelessness-climate-
    update.pdf>


    Since your career was as a consultant that required research, your
    unwillingness to acknowledge this factor speaks volumes:

    have you had significant cognitive decline to have missed such an
    clear association?

    Or were you never really good at your job?

    Or worse yet, did you know better anyway, as you you were only being
    hired because you'd deliver the conclusion that the customer wanted,
    even if it wasn't truthful?

    "Choose your poison."


    -hh

    Now you are depending on narrowing the scope to sheltered versus
    unsheltered, a different argument and a goalpost shift. But your
    argument falls totally apart when you look across the entire U.S.
    Weather is far from a consistent variable in explaining total homeless
    rates/capita.

    Nope.


    I never said weather cannot ever be a factor.


    You implied it by focusing only on housing costs.

    I looked at total homelessness in my original post. How do you explain
    dramatically lower TOTAL homeless rates across the southern states
    from Florida to Arizona than is the case in California Oregon,
    Washington, Nevada, Maine, Vermont and New York? Mississippi, with low
    household income and a nice warm climate, at 3.3, has the lowest
    rate/10,000 in the country. Why? Could housing affordability be an
    important independent variable?

    Sounds like you didn't even bother to read the cite I provided.


    Your argument that weather is a consistent factor in total homeless
    rate across the country falls apart.

    Fortunately, I wasn't claiming that it is a *consistent* factor, merely
    that it was a factor.  As per my cite, one can see that it is consistent within certain contexts though.


    So you think you know stats?

    Don't need to make that personal claim to note where another person's alleged numbers go sideways.

    Here is a problem for you. I have been tracking my electric use in
    this total electric home since 2010. Just for fun I built a regression
    model. It explains 96.5% of the variation in monthly average kWh per
    day billed.

    On October 1, 2024 we replaced our heat pump. I want to know if it
    made a difference in power use. The company that sold it to us claimed
    it would, but power savings were not the primary reason for the
    replacement.

    First, here are few facts:

    Use depends on weather, temperature to be precise, but is not linear.
    Why is it not linear?

    For a variety of factors besides just temperature, which you're trying
    to pretend you actually know.  Offhand, I can think of at least three, which I've happened to have noticed in my own bill without charts, which indicates they're not significantly lower-order variables.

    Does this have something to do with thermodynamics and heat pumps? Oh, I
    think it just might.

    A graph of local temps and kWh/day:

    https://drive.google.com/file/d/1qSiDqfp_ldcEDeovUIdkhHAV8JwsKafZ/
    view? usp=sharing

    How would you specify the functional form? Linear (Y = a + bX) will
    not work nearly as well as other functional forms. The linear R^2 is
    only 71%.
    Well, I'd not pick linear, as the upward curve on the right is increased demand from air conditioning.
    How would you correct for increasing variance (heteroskedasticity) as
    temperature falls? Why is this important?

    By not using a univariant model.

    Wrong. It's a functional form issue.

    Why do you think there are 4 major outliers?
    What actual proof do you have that there's four?

    My eyeball sees two likely ones, probably one more, but one needs to run
    a formal test with criteria to correctly assess this.  Plus after one accounts for both first & second order factors (& known nonlinearities), there very well may be zero outliers actually present.


    What other factors would you look for other than temperature? Hint, a
    much better nonlinear functional form using only temperature explains
    only 87% of dependent variable variation, about 10 points short with
    other independent variables included.

    As I said, I have some factors that on a first principles standpoint
    must be variance contributors to your model.  It seems that you've not figured them out and are trolling for free assistance, because you're
    only thinking in two dimensional space instead of more (eg, multivariate).

    No, as I stated above I and testing your knowledge. I already have the results. And have had results since Covid made me stay home and look for something interesting to do.>

    How would you determine if the new heat pump is more efficient or not
    at the 95% confidence level?
    T stat and P value for a 0,1 constant level adjuster. Where 0 = no new
    heat pump, 1 = new heat pump.


    With your present data, I wouldn't bother:  it has too much noise from ~second order variables that you've failed to control for.  One doesn't bother with the likes of a Student t until the data's clean enough to be useful. So the first real step would be to build a better model on the legacy data to replace your trash.  FYI, the t was from William Gosset,
    as he was working for Guinness & couldn't publish under his own name.

    That graph was raw data, not the predicted values from the regression.
    The regression is designed to REDUCE the variance by introducing
    orthogonal independent variables. Your ignorance is showing.


    Thanks to a new smart thermostat installed with the new heat pump I
    also now have monthly heat pump run time data from last October to
    date. How would you specify a regression between run time and kWh
    billed? Think it's linear or not? What interesting result might you see?

    Since you're ignoring several contributing variables (hence your high variance), what you'll have will be noisy & uninteresting trash.

    I await your answers. Functional form is the easiest, but not obvious.

    When you respond I'll share the actual equations based on 1/1/2010 to
    date.

    At which point I may note for myself what variables you've ignored, and which I may or may not bother to post...you going to pay my consulting fee?

    -hh

    Comments on the homeless issue later.

    You have TOTALLY missed all the modeling points. I have a model that has correctly specified the best fitting non-linear form for temperature.
    Using natural logs for the dependent variable further corrects for the non-linear relationship and reduces heteroskedasticity. This is a
    well-know regression tweak. Furthermore, billing cycle days vary. So,
    the dependent variable is ln kWh/day.

    If you know anything about heat pump (or air-conditioning for that
    matter) physics you would know why efficiency declines as temperature
    moves away from a thermally neutral 68-70 degree range show in the kWh
    versus temperature graph. Thus the somewhat U-shaped curve. Now, do you
    know why? I think not, so -

    https://learnmetrics.com/heat-pump-efficiency-vs-temperature-graph/

    The MOST obvious other independent variables are other items that might
    affect the thermal efficiency of the home. I identified vacation days
    away, Anderson replacement windows, enclosing a porch, a new more
    efficient water heater and the new heat pump. All are statistically significant at the 95% level and have the correct negative signs. None
    of these were done for energy savings, but had that in mind.

    Vacation days away reduce use for everything but the heat pump, and that
    is reduced by thermostat changes.

    The new heat pump in particular has the largest effect, a t-stat of 6.22
    and p value of 3.56E-09. Based on those stats it is the single most
    effective improvement we have made. Sorry, you were dead wrong. The
    model easily picks up the effect.

    Other result: The effect of slightly higher annual average temps and
    home improvements has been to keep our power bills almost constant since
    2010 despite rate increases. The inflation corrected cost has obviously declined over time.

    2010: 25,043 kWh, 54.7 average temp, $1,647 cost, 6.577 cents/kWh
    2024: 14,687 kWh, 56.9 average temp, $1,711 cost, 11.64 cents/kWh

    Cost is energy cost only, not including sales tax and a monthly fixed
    customer fee. Those are not affected by the independent variables, thus excluded.

    I am pretty confident that the new heat pump running for all of 2025 is
    going to keep our cost almost most flat despite a significant increase
    in average rate.

    Outliers: We had 2 winter months when the heat pump was not working. As
    in it went bad and we did not notice it right away. It was Jan-Feb and
    the backup heat runs a lot anyway. I really saw it when we got 2 large electric bills. That was 2 of the outliers, and are included in the
    model. The other 2 were both in September and included in the model. 0,1 constant level adjusters were used for these exogenous effects.

    After my last post I took some time to look at the model again and
    discovered that May-October use was lower than average, statistically significant except for July, and had negative signs. This may be a
    further artifact of a non-linear relationship.

    Here is the model:

    ln kWh use = function of:

    Intercept
    Avg Temp^2/1000
    Avg Temp^3/1000
    Winter Days Away>9
    Compressor Failure Days
    New Windows 2020
    Porch Enclosed 2014
    New Water Heater 2017
    New Heat Pump 2024
    May
    Jun
    Jul
    Aug
    Sep
    Oct
    September Outliers

    The R^2 is 96.7% and standard error reduced to 0.105 from 0.111.

    Here is a graph plotted using temperature regression coefficients versus temperature for the 10 year range of monthly averages. This verifies the functional form. It took a few iterations to get to here.

    https://drive.google.com/file/d/11f06RX4dIwmx47amZ9t8DJ6Dx0lRFWx7/view?usp=sharing

    As for the use versus run time regression it is linear. The intercept is
    kWh used with zero heat pump use and the slope is kWh per hour of use.
    R^2 = 96.7%. You can live a perfectly happy life without that knowledge,
    but I find it interesting. The graph:

    https://drive.google.com/file/d/1VoD4sJKTeZgfWClJBOUGRewoQygk_oRM/view?usp=sharing

    What have I ignored? Actual thermostat setting. Until last October when
    we put in an Ecobee thermostat there is no data. I am certain that if I
    had those data it would be very useful. As is, it is only captured in
    vacation days, and partially at that.

    I also looked at monthly sunshine hours and wind speed. Neither had a significant effect. We installed all LED lighting but I have no record
    of exactly when. We replaced all of our original kitchen appliances at
    once. I have that date and it had no significant effect.

    We have made no insulation or other weatherproofing improvements. I had
    the attic insulation inspected. It was deemed to be satisfactory.

    Here is link to a graph of raw ln kWh/day versus temperature with the
    new heat pump data points identified. Can you see why I might suspect a statistically significant effect?

    https://drive.google.com/file/d/1FWSxCOtsMmOLN8KExRJgyNvp3zmKB3uA/view?usp=drive_link

    The green point on the far left was last January. We were away most of
    the month and it was one of the coldest months in the last few decades.
    The thermostat was set to 60 versus a normal 71. We were out of town 3
    weeks last May. That is the lowest green point. The rest are at at the
    bottom of the monthly ranges.

    What else can you think of?
    --- Synchronet 3.21a-Linux NewsLink 1.2