Tarefa causcibench_real.q043

Veredito

Pergunta feita ao analista

Does smaller class sizes lead to higher scores in math tests?

Valores esperados e de onde vêm

Verificações

Caminho de referência e caminho do agente

A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.

Trajetória

Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.

1. 0Início

   Does smaller class sizes lead to higher scores in math tests?

   angrist_using_maimonides (agent)

   The dataset contains data on 5th graders enrolled in Israeli public elementary schools. The schools had imposed an upper limit on the class size of 40. In case the class size exceeds 40 students, another class is set up. To ensure balance across multiple classes of the same grade, students are split roughly evenly. In addition to including information about the school and the class size, the dataset also includes data on student performance in verbal (Hebrew reading) and mathematics tests. Variables include: schlcode: School identifier code towncode: Town identifier code townname: Town name townid: Town identifier (same as towncode) popcode: Population/administrative code used for linkage grade: Grade level (e.g., 3, 4, 5) classid: Class identifier within school and grade c_size: Total number of 5th graders in the school classize: Total number of students in each class, post-splitting if enrollment is greater than 40 c_boys: Number of boys in 5th grade c_girls: Number of girls in 5th grade c_numcl: Total number of classes in the school c_type: Total number of classes in the 5th grade cohsize: Total number of students in the 5th grade (same as c_size) classct: Count of classes in the 5th grade (same as c_num5rd) c_num5rd: Total number of classes in the 5th grade (same as c_type) mrkgrm5: Average reading (verbal) score for grade 5 ngrm5: Number of fifth-grade reading test takers nmth5: Number of fifth-grade math test takers mathsize: Number of students who took the math test in the class avgmath: Average composite math score in the class (1-100 scale) passmath: Share of students passing the math test in the class verbsize: Number of students who took the reading test in the class avgverb: Average composite reading (verbal) score in the class (1-100 scale) passverb: Share of students passing the reading (verbal) test in the class studchk: Data quality/student consistency check indicator (1 = no missing data) impute: Indicator that class-level averages were imputed from school totals tip_a: Percent of disadvantaged students (same as tip_s) tip_s: Percent of disadvantaged students tipuach: Percent of disadvantaged students (same as tip_s)

   file dc453570d77ed9822a3ba40616fc1e604dd805b036e71954a3a0bf894ca2f8b3 · frame —
2. 1Turno do modelo
   call_61bb428creferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   causcibench_metadata_rule/1: iv

   Chamadas pedidas

   • infer.iv_2sls

     {
       "dataset": "angrist_using_maimonides",
       "endog": [
         "classize"
       ],
       "exog": [
         "tipuach"
       ],
       "instruments": [
         "class_section"
       ],
       "y": "avgmath"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.iv_2slsv0.1.0call_ce9109acdecidido pelo modeloreexecutável

   Motivo: causcibench_metadata_rule/1: iv

   Argumentos

   {
     "cluster": null,
     "dataset": "angrist_using_maimonides",
     "endog": [
       "classize"
     ],
     "exog": [
       "tipuach"
     ],
     "instruments": [
       "class_section"
     ],
     "level": 0.95,
     "se": "HC1",
     "subset": null,
     "y": "avgmath"
   }

   Figuras call_ce9109ac

   Chave	Valor	Valor bruto	Erro-padrão	IC
   coef.classize 2SLS effect of classize on avgmath	0,00251872	0.0025187156424833494	0,05053520.05053517092095493	-0,0965878 – 0,101625

   Diagnósticos

   • first_stage_F.classize = 1.355,181355.1751702192244
   • partial_r2.classize = 0,4502060.4502056229987632
   • weak_instrument = false
   • n_obs = 2.0242024
   • se_type = "HC1"
   • n_clusters = —

   Tabelas (3)

   {
     "coefficients": [
       {
         "ci_high": 75.40636524114048,
         "ci_low": 68.82496533859818,
         "coef": 72.11566528986933,
         "p": 3.261940535338064e-287,
         "se": 1.6779538895084825,
         "t": 42.97833554353149,
         "term": "Intercept"
       },
       {
         "ci_high": -0.3099327340096503,
         "ci_low": -0.3808057447080057,
         "coef": -0.345369239358828,
         "p": 5.420543959652141e-75,
         "se": 0.018069353894836902,
         "t": -19.113535623291604,
         "term": "tipuach"
       },
       {
         "ci_high": 0.10162518425693252,
         "ci_low": -0.09658775297196583,
         "coef": 0.0025187156424833494,
         "p": 0.9602541422158666,
         "se": 0.05053517092095493,
         "t": 0.04984084542670337,
         "term": "classize"
       }
     ],
     "first_stage": [
       {
         "ci_high": 0.7453406674044843,
         "ci_low": 0.669943637989315,
         "coef": 0.7076421526968997,
         "endog": "classize",
         "instrument": "class_section",
         "p": 1.7714317295044745e-227,
         "se": 0.019222770328194007,
         "t": 36.812703924314285
       }
     ],
     "reduced_form": [
       {
         "ci_high": 0.07192830192532984,
         "ci_low": -0.06836360320677334,
         "coef": 0.001782349359278244,
         "instrument": "class_section",
         "p": 0.9602620896631152,
         "se": 0.03576797510694268,
         "t": 0.04983087116195975
       }
     ]
   }

   • 5 rows were dropped because one of 'avgmath', 'classize', 'class_section', 'tipuach' was missing

   Digests dos dados

   angrist_using_maimonides 872ee3e71c86dc0b6554fa04b52d9469475909091a9fd16f4e2db508d3391e3f

   sha256 do resultado

   717a1c8c0933f72525b8eb44766f7012fc8bee30bed278db37bd395e03a1e1a7

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_89310b9breferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Chamadas pedidas

   • submit_answer (meta-ferramenta)

     {
       "answer": "Estimativa (infer.iv_2sls): coef.classize = 0,002519.",
       "caveats": [],
       "figure_refs": [
         "call_ce9109ac:coef.classize"
       ]
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
5. 4Guarda
   resposta aceita

   Números encontrados

   0,002519

   Sem lastro

   —

   Não citados

   —

   1 nova(s) tentativa(s) restante(s)
6. 5Resposta

   Estimativa (infer.iv_2sls): coef.classize = 0,002519.

   Figuras citadas: call_ce9109ac:coef.classize · Parada: answered

   Figura da resposta: call_ce9109ac:coef.classize = 0,002518720.0025187156424833494 (se 0,05053520.05053517092095493)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta próximafalhouobrigatória0.002518715642 vs -0.013

Épocas × verificações

Tentativas

Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.

• época 1, tentativa 1falhoupontuada(exibindo)

Downloads desta tarefa