TEST BANK | |
Introduction to Statistical Investigations,
| | | |
2nd Edition Nathan Tintle; Beth L. Chance
| | | | | |
| Chapters 1 - 11, Complete
| | | |
FOR |INSTRUCTOR |USE |ONLY
,TABLE OF CONTENTS
| | |
Chapter 1 – Significance: How Strong is the Evidence
| | | | | | | | |
Chapter 2 – Generalization: How Broadly Do the Results Apply?
| | | | | | | | | |
Chapter 3 – Estimation: How Large is the Effect?
| | | | | | | | |
Chapter 4 – Causation: Can We Say What Caused the Effect?
| | | | | | | | | | |
Chapter 5 – Comparing Two Proportions
| | | | | |
Chapter 6 – Comparing Two Means
| | | | | |
Chapter 7 – Paired Data: One Quantitative Variable
| | | | | | | |
Chapter 8 – Comparing More Than Two Proportions
| | | | | | | |
Chapter 9 – Comparing More Than Two Means
| | | | | | | |
Chapter 10 – Two Quantitative Variables
| | | | | |
Chapter 11 – Modeling Randomness
| | | |
FOR |INSTRUCTOR |USE |ONLY
,Chapter 1 |
Note: | | |TE | = | Text |entry TE-N |= |Text |entry |- |Numeric|Ma
| = | Matching MS | = | Multiple |select
MC | = | Multiple |choice TF |= |True-False|E |=
Easy, |M |= |Medium, |H |= |Hard
|
CHAPTER 1 LEARNING OBJECTIVES
| | |
CLO1-1: |Use |the |chance |model |to |determine |whether |an |observed |statistic |is |unlikely |to |occur.
CLO1-2: |Calculate |and |interpret |a |p-value, |and |state |the |strength |of |evidence |it |provides |against|the
|null |hypothesis.
CLO1-3: |Calculate |a |standardized |statistic |for |a |single |proportion |and |evaluate |the |strength |of
|evidence | it |provides |against |a |null |hypothesis.
CLO1-4: |Describe |how |the |distance |of |the |observed |statistic |from |the |parameter |value |specified|by |the
|null |hypothesis, |sample |size, |and |one- |vs. |two-sided |tests |affect |the |strength |of |evidence
| against |the | null |hypothesis.
CLO1-5: |Describe |how |to |carry |out |a |theory-based, |one-proportion |z-test.
Section 1.1: Introduction to Chance Models
| | | | |
LO1.1-1: |Recognize |the |difference |between |parameters |and |statistics.
LO1.1-2: |Describe |how |to |use |coin |tossing |to |simulate |outcomes |from |a |chance |model |of |the |ran-|dom
|choice | between | two | events.
LO1.1-3: |Use |the |One |Proportion |applet |to |carry |out |the |coin |tossing |simulation.
LO1.1-4: |Identify |whether |or |not |study |results |are |statistically |significant |and |whether |or |not |the
|chance | model |is |a | plausible |explanation |for |the |data.
LO1.1-5: |Implement |the |3S |strategy: |find |a |statistic, |simulate |results |from |a |chance |model, |and
|comment |on |strength |of |evidence |against |observed |study |results |happening |by |chance
|alone.
LO1.1-6: |Differentiate |between |saying |the |chance |model |is |plausible |and |the |chance |model |is |the
|correct |explanation |for |the |observed |data.
FOR |INSTRUCTOR |USE |ONLY
, 1-2 Test |Bank |for |Introduction |to |Statistical |Investigations, |2nd |Edition
Questions |1 |through |4:
Do |red |uniform |wearers |tend |to |win |more |often |than |those |wearing |blue |uniforms |in
|Taekwondo |matches |where |competitors |are |randomly |assigned |to |wear |either |a |red |or |blue
|uniform? |In |a |sample |of |80 |Taekwondo |matches, |there |were |45 |matches |where |the|red
|uniform |wearer |won.
1. What |is |the |parameter |of |interest |for |this |study?
A. The |long-run |proportion |of |Taekwondo |matches |in |which |the |red |uniform |wearer
|wins
B. The |proportion |of |matches |in |which |the |red |uniform |wearer |wins |in |a |sample |of |80
|Taekwondo | matches
C. Whether |the |red |uniform |wearer |wins |a |match
D. | 0.50
Ans: |A; |LO: |1.1-1; |Difficulty: |Easy; |Type: |MC
2. What |is |the |statistic |for |this |study?
A. The |long-run |proportion |of |Taekwondo |matches |in |which |the |red |uniform |wearer
|wins
B. The |proportion |of |matches |in |which |the |red |uniform |wearer |wins |in |a |sample |of |80
|Taekwondo | matches
C. Whether |the |red |uniform |wearer |wins |a |match
D. | 0.50
Ans: |B; |LO: |1.1-1; |Difficulty: |Easy; |Type: |MC
3. Given |below |is |the |simulated |distribution |of |the |number |of |―red |wins‖ |that |could |happen |by
|chance |alone |in |a |sample |of |80 |matches. |Based |on |this |simulation, |is |our |observed |result
|statistically |significant?
A. Yes, |since |45 |is |larger |than |40.
B. Yes, |since |the |height |of |the |dotplot |above |45 |is |smaller |than |the |height |of |the
|dotplot |above |40.
C. No, |since |45 |is |a |fairly |typical |outcome |if |the |color |of |the |winner‘s |uniform |was
FOR |INSTRUCTOR |USE |ONLY
Introduction to Statistical Investigations,
| | | |
2nd Edition Nathan Tintle; Beth L. Chance
| | | | | |
| Chapters 1 - 11, Complete
| | | |
FOR |INSTRUCTOR |USE |ONLY
,TABLE OF CONTENTS
| | |
Chapter 1 – Significance: How Strong is the Evidence
| | | | | | | | |
Chapter 2 – Generalization: How Broadly Do the Results Apply?
| | | | | | | | | |
Chapter 3 – Estimation: How Large is the Effect?
| | | | | | | | |
Chapter 4 – Causation: Can We Say What Caused the Effect?
| | | | | | | | | | |
Chapter 5 – Comparing Two Proportions
| | | | | |
Chapter 6 – Comparing Two Means
| | | | | |
Chapter 7 – Paired Data: One Quantitative Variable
| | | | | | | |
Chapter 8 – Comparing More Than Two Proportions
| | | | | | | |
Chapter 9 – Comparing More Than Two Means
| | | | | | | |
Chapter 10 – Two Quantitative Variables
| | | | | |
Chapter 11 – Modeling Randomness
| | | |
FOR |INSTRUCTOR |USE |ONLY
,Chapter 1 |
Note: | | |TE | = | Text |entry TE-N |= |Text |entry |- |Numeric|Ma
| = | Matching MS | = | Multiple |select
MC | = | Multiple |choice TF |= |True-False|E |=
Easy, |M |= |Medium, |H |= |Hard
|
CHAPTER 1 LEARNING OBJECTIVES
| | |
CLO1-1: |Use |the |chance |model |to |determine |whether |an |observed |statistic |is |unlikely |to |occur.
CLO1-2: |Calculate |and |interpret |a |p-value, |and |state |the |strength |of |evidence |it |provides |against|the
|null |hypothesis.
CLO1-3: |Calculate |a |standardized |statistic |for |a |single |proportion |and |evaluate |the |strength |of
|evidence | it |provides |against |a |null |hypothesis.
CLO1-4: |Describe |how |the |distance |of |the |observed |statistic |from |the |parameter |value |specified|by |the
|null |hypothesis, |sample |size, |and |one- |vs. |two-sided |tests |affect |the |strength |of |evidence
| against |the | null |hypothesis.
CLO1-5: |Describe |how |to |carry |out |a |theory-based, |one-proportion |z-test.
Section 1.1: Introduction to Chance Models
| | | | |
LO1.1-1: |Recognize |the |difference |between |parameters |and |statistics.
LO1.1-2: |Describe |how |to |use |coin |tossing |to |simulate |outcomes |from |a |chance |model |of |the |ran-|dom
|choice | between | two | events.
LO1.1-3: |Use |the |One |Proportion |applet |to |carry |out |the |coin |tossing |simulation.
LO1.1-4: |Identify |whether |or |not |study |results |are |statistically |significant |and |whether |or |not |the
|chance | model |is |a | plausible |explanation |for |the |data.
LO1.1-5: |Implement |the |3S |strategy: |find |a |statistic, |simulate |results |from |a |chance |model, |and
|comment |on |strength |of |evidence |against |observed |study |results |happening |by |chance
|alone.
LO1.1-6: |Differentiate |between |saying |the |chance |model |is |plausible |and |the |chance |model |is |the
|correct |explanation |for |the |observed |data.
FOR |INSTRUCTOR |USE |ONLY
, 1-2 Test |Bank |for |Introduction |to |Statistical |Investigations, |2nd |Edition
Questions |1 |through |4:
Do |red |uniform |wearers |tend |to |win |more |often |than |those |wearing |blue |uniforms |in
|Taekwondo |matches |where |competitors |are |randomly |assigned |to |wear |either |a |red |or |blue
|uniform? |In |a |sample |of |80 |Taekwondo |matches, |there |were |45 |matches |where |the|red
|uniform |wearer |won.
1. What |is |the |parameter |of |interest |for |this |study?
A. The |long-run |proportion |of |Taekwondo |matches |in |which |the |red |uniform |wearer
|wins
B. The |proportion |of |matches |in |which |the |red |uniform |wearer |wins |in |a |sample |of |80
|Taekwondo | matches
C. Whether |the |red |uniform |wearer |wins |a |match
D. | 0.50
Ans: |A; |LO: |1.1-1; |Difficulty: |Easy; |Type: |MC
2. What |is |the |statistic |for |this |study?
A. The |long-run |proportion |of |Taekwondo |matches |in |which |the |red |uniform |wearer
|wins
B. The |proportion |of |matches |in |which |the |red |uniform |wearer |wins |in |a |sample |of |80
|Taekwondo | matches
C. Whether |the |red |uniform |wearer |wins |a |match
D. | 0.50
Ans: |B; |LO: |1.1-1; |Difficulty: |Easy; |Type: |MC
3. Given |below |is |the |simulated |distribution |of |the |number |of |―red |wins‖ |that |could |happen |by
|chance |alone |in |a |sample |of |80 |matches. |Based |on |this |simulation, |is |our |observed |result
|statistically |significant?
A. Yes, |since |45 |is |larger |than |40.
B. Yes, |since |the |height |of |the |dotplot |above |45 |is |smaller |than |the |height |of |the
|dotplot |above |40.
C. No, |since |45 |is |a |fairly |typical |outcome |if |the |color |of |the |winner‘s |uniform |was
FOR |INSTRUCTOR |USE |ONLY
