• ¿Documento equivocado? Cámbialo gratis
  • Escrito por estudiantes que aprobaron
  • Inmediatamente disponible después del pago
  • Leer en línea o como PDF
Vender
¿Dónde estudias?
Tu idioma
Document preview thumbnail
Vista previa 4 fuera de 341 páginas
Examen

TEST BANK Introduction to Statistical Investigations, 2nd Edition Nathan Tintle; Beth L. Chance Chapters 1 - 11, Complete

Document preview thumbnail
Vista previa 4 fuera de 341 páginas

TEST BANK Introduction to Statistical Investigations, 2nd Edition Nathan Tintle; Beth L. Chance Chapters 1 - 11, Complete

Vista previa del contenido

TEST BANK nn nn




Introduction to Statistical Investigations,
nn nn nn nn




nd
2 Edition Nathan Tintle; Beth L. Chance
nn nn nn nn nn nn




Chapters 1 - 11, Complete
nn nn nn nn nn




FOR INSTRUCTOR USE
nn nn



ONLY

,TABLE OF CONTENTS
nn nn nn




Chapter 1 – Significance: How Strong is the Evidence
nn nn nn nn nn nn nn nn nn




Chapter 2 – Generalization: How Broadly Do the Results Apply?
nn nn nn nn nn nn nn nn nn nn




Chapter 3 – Estimation: How Large is the Effect?
nn nn nn nn nn nn nn nn nn




Chapter 4 – Causation: Can We Say What Caused the Effect?
nn nn nn nn nn nn nn nn nn nn nn




Chapter 5 – Comparing Two Proportions
nn nn nn nn nn nn




Chapter 6 – Comparing Two Means
nn nn nn nn nn nn




Chapter 7 – Paired Data: One Quantitative Variable
nn nn nn nn nn nn nn nn




Chapter 8 – Comparing More Than Two Proportions
nn nn nn nn nn nn nn nn




Chapter 9 – Comparing More Than Two Means
nn nn nn nn nn nn nn nn




Chapter 10 – Two Quantitative Variables
nn nn nn nn nn nn




Chapter 11 – Modeling Randomness
nn nn nn nn




FOR INSTRUCTOR USE
nn nn



ONLY

,Chapter 1 n n




Note: nn nn nn TE = n n n n Text entry nn TE-N = Text entry - nn nn nn nn




nn NumericMa = n n n n n Matching MS = Multiple select
n n nn nn




MC = n n n n Multiple choice nn TF = True-FalseE
nn nn n




nn = Easy, M = Medium, H = Hard
nn nn nn nn nn nn nn




CHAPTER 1 LEARNING OBJECTIVES nn nn nn




CLO1-1: Use the chance model to determine whether an observed statistic is unlikely to occur.
nn nn nn nn nn nn nn nn nn nn nn nn nn nn




CLO1-2: Calculate and interpret a p-value, and state the strength of evidence it provides againstthe
nn nn nn nn nn nn nn nn nn nn nn nn nn nn n



null hypothesis.
nn nn




CLO1-3: Calculate a standardized statistic for a single proportion and evaluate the strength
nn nn nn nn nn nn nn nn nn nn nn nn



ofevidence it provides against a null hypothesis.
nn n nn nn nn nn nn nn




CLO1-4: Describe how the distance of the observed statistic from the parameter value specifiedby
nn nn nn nn nn nn nn nn nn nn nn nn nn n



the null hypothesis, sample size, and one- vs. two-sided tests affect the strength of evidence
nn nn nn nn nn nn nn nn nn nn nn nn nn nn nn



against the null hypothesis.
nn nn nn nn




CLO1-5: Describe how to carry out a theory-based, one-proportion z-test.
nn nn nn nn nn nn nn nn nn




Section 1.1: Introduction to Chance Models nn nn nn nn nn




LO1.1-1: Recognize the difference between parameters and statistics.
nn nn nn nn nn nn nn




LO1.1-2: Describe how to use coin tossing to simulate outcomes from a chance model of the ran-
nn nn nn nn nn nn nn nn nn nn nn nn nn nn nn nn



dom choice between two events.
n nn nn nn nn




LO1.1-3: Use the One Proportion applet to carry out the coin tossing simulation.
nn nn nn nn nn nn nn nn nn nn nn nn




LO1.1-4: Identify whether or not study results are statistically significant and whether or not
nn nn nn nn nn nn nn nn nn nn nn nn nn



thechance model is a plausible explanation for the data.
nn n nn nn nn nn nn nn nn nn




LO1.1-5: Implement the 3S strategy: find a statistic, simulate results from a chance model,
nn nn nn nn nn nn nn nn nn nn nn nn nn



andcomment on strength of evidence against observed study results happening by chance
nn n nn nn nn nn nn nn nn nn nn nn nn



alone. nn




LO1.1-6: Differentiate between saying the chance model is plausible and the chance model is
nn nn nn nn nn nn nn nn nn nn nn nn nn



thecorrect explanation for the observed data.
nn n nn nn nn nn nn




FOR INSTRUCTOR USE nn nn



ONLY

, 1-2 Test Bank for Introduction to Statistical Investigations, 2nd Edition
nn nn nn nn nn nn nn nn




Questions 1 through 4:
nn nn nn




Do red uniform wearers tend to win more often than those wearing blue uniforms in
nn nn nn nn nn nn nn nn nn nn nn nn nn nn



Taekwondo matches where competitors are randomly assigned to wear either a red or blue
nn nn nn nn nn nn nn nn nn nn nn nn nn nn



uniform? In a sample of 80 Taekwondo matches, there were 45 matches where thered
nn nn nn nn nn nn nn nn nn nn nn nn nn nn n



uniform wearer won.
nn nn nn




1. What is the parameter of interest for this study?
nn nn nn nn nn nn nn nn




A. The long-run proportion of Taekwondo matches in which the red uniform
nn nn nn nn nn nn nn nn nn nn



wearerwins nn n




B. The proportion of matches in which the red uniform wearer wins in a sample of
nn nn nn nn nn nn nn nn nn nn nn nn nn nn



80Taekwondo matches
nn n nn




C. Whether the red uniform wearer wins a match nn nn nn nn nn nn nn




D. 0.50 nn




Ans: A; LO: 1.1-1; Difficulty: Easy; Type: MC
nn nn nn nn nn nn nn




2. What is the statistic for this study?
nn nn nn nn nn nn




A. The long-run proportion of Taekwondo matches in which the red uniform
nn nn nn nn nn nn nn nn nn nn



wearerwins nn n




B. The proportion of matches in which the red uniform wearer wins in a sample of
nn nn nn nn nn nn nn nn nn nn nn nn nn nn



80Taekwondo matches
nn n nn




C. Whether the red uniform wearer wins a match nn nn nn nn nn nn nn




D. 0.50 nn




Ans: B; LO: 1.1-1; Difficulty: Easy; Type: MC
nn nn nn nn nn nn nn




3. Given below is the simulated distribution of the number of ―red wins‖ that could happen
nn nn nn nn nn nn nn nn nn nn nn nn nn nn



by chance alone in a sample of 80 matches. Based on this simulation, is our observed result
nn n nn nn nn nn nn nn nn nn nn nn nn nn nn nn nn



statistically significant?
nn nn




A. Yes, since 45 is larger than 40. nn nn nn nn nn nn




B. Yes, since the height of the dotplot above 45 is smaller than the height of
nn nn nn nn nn nn nn nn nn nn nn nn nn nn



thedotplot above 40.
nn n nn nn




C. No, since 45 is a fairly typical outcome if the color of the winner‘s uniform
nn nn nn nn nn nn nn nn nn nn nn nn nn nn



FOR INSTRUCTOR USE nn nn



ONLY

Libro relacionado
 image
Nathan Tintle, Beth L. Chance, George W. Cobb, Allan J. Rossman, Soma Roy, Todd Swanson, Jill VanderStoep Introduction to Statistical Investigations
Editorial: 2020 ISBN: 9781119683452 Edición: Desconocido

Información del documento

Subido en
5 de julio de 2025
Número de páginas
341
Escrito en
2024/2025
Tipo
Examen
Contiene
Preguntas y respuestas
$16.49

¿Documento equivocado? Cámbialo gratis Dentro de los 14 días posteriores a la compra y antes de descargarlo, puedes elegir otro documento. Puedes gastar el importe de nuevo.
Escrito por estudiantes que aprobaron
Inmediatamente disponible después del pago
Leer en línea o como PDF

Seller avatar
Los indicadores de reputación están sujetos a la cantidad de artículos vendidos por una tarifa y las reseñas que ha recibido por esos documentos. Hay tres niveles: Bronce, Plata y Oro. Cuanto mayor reputación, más podrás confiar en la calidad del trabajo del vendedor.
PageTurners
3.0
(2)
Vendido
13
Seguidores
0
Artículos
1609
Última venta
8 meses hace



Por qué los estudiantes eligen Stuvia

Creado por compañeros estudiantes, verificado por reseñas

Calidad en la que puedes confiar: escrito por estudiantes que aprobaron y evaluado por otros que han usado estos resúmenes.

¿No estás satisfecho? Elige otro documento

¡No te preocupes! Puedes elegir directamente otro documento que se ajuste mejor a lo que buscas.

Paga como quieras, empieza a estudiar al instante

Sin suscripción, sin compromisos. Paga como estés acostumbrado con tarjeta de crédito y descarga tu documento PDF inmediatamente.

Student with book image

“Comprado, descargado y aprobado. Así de fácil puede ser.”

Alisha Student

Preguntas frecuentes