Test Bank for Stats, Data and Models, 4th Canadian Edition De Veaux (All Chapters included)
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Business Statistics
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Business Statistics
Complete Test Bank for Stats, Data and Models, 4th Canadian Edition by Richard D. De Veaux, Paul F. Velleman, David E. Bock, Augustin M. Vukov, Augustine Wong ; ISBN13: 9780137364626. (Full Chapters included Chapter 1 to 29)....0.Stats Starts Here
1.Displaying and Describing Categorical Data
2.Di...
Richard D. De Veaux, Williams College
Paul F. Velleman, Cornell University (Emeritus)
David E. Bock, Cornell University/Ithaca High School (Retired)
Augustin M. Vukov, University of Toronto
Augustine C. M. Wong, York University
Complete Chapter Test Bank
are included (Ch 1 to 29)
** Immediate Download
** Swift Response
** All Chapters included
, Contents
Chapter 1: Stats Starts Here
Chapter 2: Displaying and Describing Categorical Data
Chapter 3: Displaying and Summarizing Quantitative Data
Chapter 4: Understanding and Comparing Distributions
Chapter 5: The Standard Deviation as a Ruler and the Normal Model
Chapter 6: Scatterplots, Association, and Correlation
Chapter 7: Linear Regression
Chapter 8: Regression Wisdom
Chapter 9: Sample Surveys
Chapter 10: Experiments and Observational Studies
Chapter 11: From Randomness to Probability
Chapter 12: Probability Rules!
Chapter 13: Random Variables
Chapter 14: Sampling Distribution Models
Chapter 15: Confidence Intervals for Proportions
Chapter 16: Testing Hypotheses About Proportions
Chapter 17: More About Tests
Chapter 18: Inferences About Means
Chapter 19: Comparing Means
Chapter 20: Paired Samples and Blocks
Chapter 21: Comparing Two Proportions
Chapter 22: Comparing Counts
Chapter 23: Inferences for Regression
Chapter 24: Analysis of Variance
Chapter 25: Multifactor Analysis of Variance
Chapter 26: Multiple Regression
Chapter 27: Multiple Regression Wisdom
Chapter 28: Nonparametric Tests
Chapter 29: The Bootstrap
,Stats: Data and Models, 4ce (De Veaux)
Chapter 1 Stats Starts Here
1.1 What is Statistics?
1) True or False: Data are always numbers.
Answer: FALSE
Diff: 1 Type: TF
Objective: (1.1) What is Statistics?
2) True or False: Individuals can be statistics.
Answer: FALSE
Diff: 1 Type: TF
Objective: (1.1) What is Statistics?
3) Is the statement below a correct use of the word "statistics"? If not, why?
"Don't drink and drive; you don't want to be a statistic."
Answer: No. Individuals cannot be statistics.
Diff: 1 Type: SA
Objective: (1.1) What is Statistics?
1.2 Data
1) Identify the W's for the description of data.
A survey of bicycles parked outside student residences at a university recorded the style
(mountain bike, ten speed, etc.), the brand, the color, and the age.
A) Who: Student residences.; Cases: Each student residence is a case; What: Type of student
residence; When: Not specified; Where: A university; Why: Not specified; How: A survey was
taken outside student residences.
B) Who: Bicycles parked on campus; Cases: Each bicycle is a case; What: Style, brand, color,
and age of bicycle; When: Not specified; Where: A university; Why: Class Assignment; How: A
survey was taken outside classrooms.
C) Who: Bicycles parked outside student residences.; Cases: Each bicycle is a case; What: Style,
brand, color, and age of bicycle; When: Not specified; Where: A university; Why: Not specified;
How: A survey was taken outside student residences.
D) Who: Bicycles parked outside student residences; Cases: Each bicycle is a case; What:
Mountain bikes, ten speeds; When: Not specified; Where: A university; Why: Not specified;
How: Students were asked about the bicycle they ride.
E) Who: Student residences.; Cases: Each student residences is a case; What: Size of student
residence; When: During fall semester; Where: A university; Why: Not specified; How: A
survey was taken outside student residences.
Answer: C
Diff: 1 Type: BI
Objective: (1.2) Determine the W's for a Description of Data
, 2) Identify the W's for the description of data.
A university requires coaches to keep these records on all athletes: age, days absent, medical
history, emergency contact, and any allergies the athlete may have.
A) Who: Athletes at the university; Cases: Each athlete is an individual case; What: Age, days
absent, medical history, emergency contact, and allergy history; When: Current; Where: Not
specified; Why: University requirement; How: Information is collected and stored as athletic
records.
B) Who: The University; Cases: Each athlete is an individual case; What: Records; When:
Current; Where: Not specified; Why: University requirement; How: Information is collected and
stored as athletic records.
C) Who: Coaches at the university; Cases: Each team is an individual case; What: Age, days
absent, medical history, emergency contact, and allergy history; When: Current; Where: Not
specified; Why: University requirement; How: Information is collected and stored as athletic
records.
D) Who: Athletes at the university; Cases: Each athlete is an individual case; What: Years
played, sport played, and position played; When: Current; Where: Not specified; Why:
University requirement; How: Information is collected and stored as athletic records.
E) Who: Athletes at the university; Cases: Each athlete is an individual case; What: Records;
When: Current; Where: Not specified; Why: Helpful information; How: Ask the athlete.
Answer: A
Diff: 1 Type: BI
Objective: (1.2) Determine the W's for a Description of Data
3) Identify the W's for the description of data.
In 2017, a soft drink company trying to find ways to boost sales over their competitors compiled
these data about consumers: age, weekly consumption, diet vs. regular preference, cola vs non-
cola preference, and geographical location.
A) Who: Soft drink companies; Cases: Each company is a case; What: Age, weekly
consumption, diet vs. regular preference, cola vs. non-cola preference, and geographical location;
When: June, 2017; Where: United States; Why: To find ways to boost sales.
B) Who: Consumers; Cases: Each consumer is a case; What: Age, weekly consumption, diet vs.
regular preference, cola vs. non-cola preference, and geographical location; When: 2017; Where:
Not specified; Why: To find ways to boost sales.
C) Who: Consumers; Cases: Each consumer is a case; What: Age; When: 2017; Where: Not
specified; Why: To find ways to boost sales.
D) Who: Consumers; Cases: Each consumer is a case; What: Age, weekly consumption, and
geographical location; When: 2017; Where: Not specified; Why: To develop new products.
E) Who: Soft drink companies; Cases: Each company is a case; What: Age, weekly
consumption, diet vs. regular preference, cola vs. non-cola preference, and geographical location;
When: 2017; Where: Not specified; Why: To find ways to boost sales.
Answer: B
Diff: 1 Type: BI
Objective: (1.2) Determine the W's for a Description of Data
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