Tarefa paper_repro.stock_watson_caschool.tab7_1_c2.design
paper_reproagentT3designépoca 1, tentativa 1Execução: 20261015T165744Z-suite-paper_repro-scripted-def9dfVeredito
Família do método (das chamadas de ferramentas): ols (regression)
Pergunta feita ao analista
Holding constant the share of students who are still learning English, do California school districts with fewer students per teacher have higher test scores? Report the change in the district's average test score associated with one more student per teacher.
Estimativa (infer.ols): coef.str = -1,101.
Valores esperados e de onde vêm
stock_watson_caschool.tab7_1_c2.software
- Fonte
- statsmodels 0.15.0: the reference specification of stock_watson_caschool tab7_1_c2 (infer.ols, figure 'coef.str') on an independent code path
- Tipo
- software
- Localização
- stock_watson_caschool: Table 7.1 (class size and test scores), column (2), row 'Student-teacher ratio (X1)'; the regression adding the percentage of English learners
- Valor
- -1,1013
-1.1012958888674582(se 0,4328470.4328471535415152) - Conferido por
- execução de software · sm.OLS(testscr, add_constant(['str', 'elpct'])).fit(cov_type='HC1') on caschool (the file pinned at sha256 644e606cd8ff21557375a091f744f623323bb84de99da616923a97942e4fe54b); n_obs = 420. The tool infer.ols (magi_infer, numpy) does not call statsmodels. Written by scripts/paper_repro_reference.py.
- Implementação
- independente da ferramenta
- Endereço
https://pypi.org/project/statsmodels/0.15.0/
- #7 figura da resposta próxima: -1,1013
-1.1012958888674582· relativa 0.000001 · absoluta 4.3284715354151516e-7 - #8 figura da resposta próxima: 0,432847
0.4328471535415152· relativa 0.000001 · absoluta 4.3284715354151516e-7
stock_watson_caschool.tab7_1_c2.paper
- Fonte
- Stock, J. H. and Watson, M. W. (2015). Introduction to Econometrics, 3rd edition (update). Boston: Pearson.
- Tipo
- textbook
- Localização
- Table 7.1 (class size and test scores), column (2), row 'Student-teacher ratio (X1)'; the regression adding the percentage of English learners
- Página
- slides 4 and 52 of the NTU reproduction (book page not read)
- Trecho
(2) TestScore = − 1.10 ⋅ STR − 0.650 ⋅ PctEL (0.43) (0.031)
- Valor como publicado
−1.10- Erro-padrão como publicado
0.43- Valor
- -1,1
-1.1(se 0,430.43) test-score points per student per teacher - Conferido por
- fonte secundária · The book itself was not read (not public). Secondary reproduction read on 2026-10-15: Ming-Ching Luoh's course slides 'Linear Regression with Multiple Regressors: Hypothesis Tests' (National Taiwan University, 2022; multiple2.pdf, sha256 0d9f829e...), slide 4, which reprints the book's two California class-size equations with standard errors under the coefficients, (1) 698.9 - 2.28 STR (10.4) (0.52) and (2) ... - 1.10 STR - 0.650 PctEL (8.7) (0.43) (0.031), and slide 52, which calls equation (2) 'Model (2) of Table 7.1'. The same deck prints the intercept of (2) as 696.0 where other reproductions print 686.0, so the deck is not free of typos; the STR cells agree with Giannakopoulos's slides (University of Patras, 2024, Lecture_2.pdf sha256 660d787c..., slide 23: 698.9 - 2.28 STR, (10.4) (0.52)). The book reports heteroskedasticity-robust standard errors throughout these chapters (Stata 'robust', HC1). Equation numbers differ by edition (research-papers.md section 3.6: (4.11) in older editions, (5.8) in later ones); the equation number was not confirmed against the book.
- sha256 da cópia lida
0d9f829ec53dfbdb4296d182f66c03263090f1044053f74ce9984101d33ec889(identifica a cópia lida, não um arquivo canônico)- Endereço
https://homepage.ntu.edu.tw/~luohm/metrics2022s/multiple2.pdf- Licença
- Copyright Pearson Education; cited, not reproduced.
- #9 figura da resposta próxima: -1,1
-1.1· published_cell d=2 · absoluta 0.0050000011 - #10 figura da resposta próxima: 0,43
0.43· published_cell d=2 (the SE as printed) · absoluta 0.0050000010000000004
Verificações
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | resposta com lastro every number backed | obrigatória | passou | — | [] | — | — | — |
| 1 | figura da resposta escolhida answer figure call_aefeedc8:coef.str (infer.ols) | obrigatória | passou | — | "call_aefeedc8:coef.str" | — | — | call_aefeedc8 |
| 2 | ferramenta chamada answer call is infer.ols | obrigatória | passou | — | "infer.ols" | — | — | call_aefeedc8 |
| 3 | argumento igual infer.ols.y = 'testscr' | obrigatória | passou | "testscr" | "testscr" | — | — | call_aefeedc8 |
| 4 | argumento igual infer.ols.x[0] = 'str' | obrigatória | passou | "str" | "str" | — | — | call_aefeedc8 |
| 5 | argumento igual infer.ols.y = 'testscr' | registrada | passou | "testscr" | "testscr" | — | — | call_aefeedc8 |
| 6 | diagnóstico 420 vs 420 | registrada | passou | 420420 | 420420 | default rel 1e-6 (abs floor 1e-6) | — | call_aefeedc8 |
| 7 | figura da resposta próxima -1.101295889 vs -1.1012958888674582 | registrada | passou | -1,1013-1.1012958888674582 | -1,1013-1.1012958888676343 | relativa 0.000001 · absoluta 4.3284715354151516e-7 | stock_watson_caschool.tab7_1_c2.software | call_aefeedc8 |
| 8 | figura da resposta próxima 0.4328471535 vs 0.4328471535415152 | registrada | passou | 0,4328470.4328471535415152 | 0,4328470.43284715354151615 | relativa 0.000001 · absoluta 4.3284715354151516e-7 | stock_watson_caschool.tab7_1_c2.software | call_aefeedc8 |
| 9 | figura da resposta próxima -1.101295889 vs -1.1 | registrada | passou | -1,1-1.1 | -1,1013-1.1012958888676343 | published_cell d=2 · absoluta 0.0050000011 | stock_watson_caschool.tab7_1_c2.paper | call_aefeedc8 |
| 10 | figura da resposta próxima 0.4328471535 vs 0.43 | registrada | passou | 0,430.43 | 0,4328470.43284715354151615 | published_cell d=2 (the SE as printed) · absoluta 0.0050000010000000004 | stock_watson_caschool.tab7_1_c2.paper | call_aefeedc8 |
Caminho de referência e caminho do agente
A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.
a tarefa T1 do mesmo alvo (paper_repro.stock_watson_caschool.tab7_1_c2.tool)
| Argumento | Referência | Agente | |
|---|---|---|---|
| cluster | — | — | não fixado pela referência |
| controls | ["elpct"] | ["elpct"] | igual |
| dataset | "caschool" | "caschool" | igual |
| fe | [] | [] | igual |
| intercept | — | true | não fixado pela referência |
| level | — | 0,950.95 | não fixado pela referência |
| se | "HC1" | "HC1" | igual |
| subset | — | — | não fixado pela referência |
| weights | — | — | não fixado pela referência |
| x | ["str"] | ["str"] | igual |
| y | "testscr" | "testscr" | igual |
Trajetória
Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.
- 0Início
Holding constant the share of students who are still learning English, do California school districts with fewer students per teacher have higher test scores? Report the change in the district's average test score associated with one more student per teacher.
caschool(agent)Stock and Watson's California Test Score data (R package Ecdat, Caschool): one row per California K-6 or K-8 school district, 1998-1999 (420 rows). Columns: rownames, a row number; distcod, district code; county; district, district name; grspan, grade span; enrltot, total enrolment; teachers, number of teachers; calwpct, percent of students qualifying for CalWORKs; mealpct, percent qualifying for reduced-price lunch; computer, number of computers; testscr, average test score (the average of readscr and mathscr); compstu, computers per student; expnstu, expenditure per student (dollars); str, student-teacher ratio (enrltot / teachers); avginc, district average income (thousands of dollars); elpct, percent of students who are English learners; readscr, average reading score; mathscr, average math score.
file644e606cd8ff21557375a091f744f623323bb84de99da616923a97942e4fe54b· frame — - 1Turno do modelo
call_292f9ddfreferenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheTexto visívelTable 7.1, column (2): OLS of district test scores on the student-teacher ratio and the percentage of English learners, heteroskedasticity-robust (HC1) errors.
Chamadas pedidasinfer.ols{ "controls": [ "elpct" ], "dataset": "caschool", "fe": [], "se": "HC1", "x": [ "str" ], "y": "testscr" }
- 2Ferramenta
infer.olsv0.1.0call_aefeedc8decidido pelo modeloreexecutávelMotivo: Table 7.1, column (2): OLS of district test scores on the student-teacher ratio and the percentage of English learners, heteroskedasticity-robust (HC1) errors.
Argumentos
{ "cluster": null, "controls": [ "elpct" ], "dataset": "caschool", "fe": [], "intercept": true, "level": 0.95, "se": "HC1", "subset": null, "weights": null, "x": [ "str" ], "y": "testscr" }Figuras call_aefeedc8 Chave Valor Valor bruto Erro-padrão IC coef.str Coefficient on str in the regression of testscr-1,1013 -1.10129588886763430,432847 0.43284715354151615-1,95213 – -0,250462 Diagnósticosn_obs= 420420k= 33r2= 0,4264310.4264313614327725df_resid= 417417se_type="HC1"n_clusters= —
Tabelas (1)
{ "coefficients": [ { "ci_high": 703.1890488944882, "ci_low": 668.8754484743192, "coef": 686.0322486844037, "p": 3.979923074299225e-252, "se": 8.728223769944982, "t": 78.59929657700883, "term": "Intercept" }, { "ci_high": -0.25046159192998885, "ci_low": -1.9521301858052797, "coef": -1.1012958888676343, "p": 0.01130918244150866, "se": 0.43284715354151615, "t": -2.544306644636406, "term": "str" }, { "ci_high": -0.5887785969739106, "ci_low": -0.7107749563323569, "coef": -0.6497767766531337, "p": 4.6994747143062855e-67, "se": 0.03103176322392732, "t": -20.93908657282218, "term": "elpct" } ] }- Digests dos dados
caschoolbcde4818bfe3a91ac2a79e27a21e90c7ea258921b02fffe83f56764a05da8dae- sha256 do resultado
32bba7a2a56e656e5402e8b3110c023265578b2ddf69291de7c5ddcfb91d0357
- 3Turno do modelo
call_02642b3freferenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheChamadas pedidassubmit_answer(meta-ferramenta){ "answer": "Estimativa (infer.ols): coef.str = -1,101.", "caveats": [], "figure_refs": [ "call_aefeedc8:coef.str" ] }
- 4Guardaresposta aceita
- Números encontrados
- -1,101
- Sem lastro
- —
- Não citados
- —
1 nova(s) tentativa(s) restante(s) - 5Resposta
Estimativa (infer.ols): coef.str = -1,101.
Figuras citadas:call_aefeedc8:coef.str· Parada:answeredFigura da resposta:call_aefeedc8:coef.str= -1,1013-1.1012958888676343(se 0,4328470.43284715354151615) - 6Pontuação#0resposta com lastropassouobrigatória
every number backed - 7Pontuação#1figura da resposta escolhidapassouobrigatória
answer figure call_aefeedc8:coef.str (infer.ols) - 8Pontuação#2ferramenta chamadapassouobrigatória
answer call is infer.ols - 9Pontuação#3argumento igualpassouobrigatória
infer.ols.y = 'testscr' - 10Pontuação#4argumento igualpassouobrigatória
infer.ols.x[0] = 'str' - 11Pontuação#5argumento igualpassouregistrada
infer.ols.y = 'testscr' - 12Pontuação#6diagnósticopassouregistrada
420 vs 420 - 13Pontuação#7figura da resposta próximapassouregistrada
-1.101295889 vs -1.1012958888674582 - 14Pontuação#8figura da resposta próximapassouregistrada
0.4328471535 vs 0.4328471535415152 - 15Pontuação#9figura da resposta próximapassouregistrada
-1.101295889 vs -1.1 - 16Pontuação#10figura da resposta próximapassouregistrada
0.4328471535 vs 0.43
Épocas × verificações
| # | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Época 1 | passou | passou | passou | passou | passou | passou | passou | passou | passou | passou | passou |
Tentativas
Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.
- época 1, tentativa 1passoupontuada(exibindo)
Downloads desta tarefa
696a45c0b391c155d0d51d6f5498ecbecbcdb4fdddd2ed0a082fc9e148ed868fO hash de um zip é só de transporte: o que ancora a integridade é o RUN_SHA256SUMS que vai dentro dele, cópia exata do SHA256SUMS da execução.
| Arquivo | Tamanho | sha256 |
|---|---|---|
| attachments/29cb4c6d52d4de42aaaa987e3f07ac48016cc6cb8772773c13f57c4728965ebe.json | 1,1 KB | 29cb4c6d52d4de42aaaa987e3f07ac48016cc6cb8772773c13f57c4728965ebe |
| attachments/433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420.json | 2,4 KB | 433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420 |
| attachments/52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b.json | 64,0 KB | 52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b |
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| sources/stock_watson_caschool.tab7_1_c2.paper.json | 2,2 KB | 41ed68b5decc66e0b5536839578329ad452936ce1aa908637dc33a0b32f087c6 |
| sources/stock_watson_caschool.tab7_1_c2.software.json | 1,2 KB | abd36610492cf6d7cad91d699b56342e739202eceea03fb73eee9f5295b0ebe9 |
| specs/paper_repro.stock_watson_caschool.tab7_1_c2.design.json | 8,0 KB | 51368cb1b18eb5c6373f2138c63673d98c13481c4a7450a52a8e1ba9b5fe30ba |
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