The Practice of Statistics - Ms. Cowart's Teacher Page



Chapter 1: Stats Starts Here

Chapter 2: Data

Key Vocabulary:

|Statistics |participant |variable |

|context |experimental unit |units |

|data, datum |observation |individual |

|cases |representative |variable |

|respondent |sample |categorical |

|subject |population |quantitative |

Calculator Skills:

|enter data in a list |name a new list |recreate a list |

|change a datum |clear a list |copy a list |

|delete a datum |delete a list | |

1. Name three things you learned about Statistics in Chapter 1.

2. The authors claim that this book is very different from a typical mathematics textbook. Would you agree or disagree, based on what you read in Chapter 1? Explain.

3. According to the authors, what are the “three simple steps to doing Statistics right?”

4. What do the authors refer to as the “W’s of data?”

5. Why must data be in context (the W’s)?

Chapter 3: Displaying and Describing Categorical Data

Key Vocabulary:

|frequency table |pie chart |conditional distribution |

|relative frequency table |categorical data condition |independence |

|distribution |contingency table |segmented bar chart |

|area principle |marginal distribution |Simpson’s Paradox |

|bar chart | | |

1. According to the authors, what are the three rules of data analysis?

2. Explain the difference between a frequency table and a relative frequency table.

3. What is the area principle?

4. When is it appropriate to use a bar chart?

5. When is it appropriate to use a pie chart?

6. When is it appropriate to use a contingency table?

7. What does a marginal distribution show?

8. When is it appropriate to look at a conditional distribution?

9. What does it mean for two variables to be independent?

10. How does a segmented bar chart compare to a pie chart?

11. Explain what is meant by Simpson’s Paradox.

Chapter 4: Displaying and Summarizing Quantitative Data

Key Vocabulary:

|distribution |unimodal |range |

|histogram |bimodal |quartile |

|relative frequency histogram |multimodal |interquartile range (IQR) |

|gap |uniform |percentile |

|stem-and-leaf display |symmetric |5-number summary |

|dotplot |tail |mean |

|shape |skewed |resistant |

|center |outliers |variance |

|spread |median |standard deviation |

|mode | | |

Calculator Skills:

| display a histogram | Display 1-Var Stats | |

1. What is meant by a distribution?

2. Explain the difference between a histogram and a relative frequency histogram.

3. In what ways are histograms similar to stem-and-leaf displays?

4. Name some advantages of stem-and-leaf displays.

5. When is it more appropriate to use a histogram rather than a stem-and-leaf display?

6. Name some advantages of dotplots.

7. When describing a distribution, what three things should you always mention?

8. What should you look for when describing the shape of a distribution (try to find five things)?

9. In general, what is meant by the center of a distribution?

10. In general, what is meant by the spread of a distribution?

11. What is a better way to describe the spread of a distribution?

12. What is meant by the 5-number summary?

13. When is it more appropriate to use the mean as a measure of center rather than the median?

14. What does referring to the median as a resistant measure indicate?

15. When is it more appropriate to use the median as a measure of center rather than the mean?

16. Why is the standard deviation considered a more powerful approach to summarizing the spread?

17. What is the relationship between the variance and the standard deviation?

18. When many data values are far from the center of a distribution, how will this be reflected in the standard deviation and the IQR?

19. What is the danger in summarizing a variable with the mean and the standard deviation?

Chapter 5: Understanding and Comparing Distributions

Key Vocabulary:

|boxplot |far outlier |comparing boxplots |

|outlier |comparing distributions |timeplot |

Calculator Skills:

| modified boxplots |ZoomStat | |

19. What is meant by an upper fence and lower fence?

20. How are outliers determined?

21. What should you look for when comparing two histograms?

22. What should you look for when comparing two or more boxplots?

23. What does the text recommend we “do” with outliers?

24. What should we never do with outliers?

25. What is a timeplot?

26. Why is skewed data sometimes re-expressed using a mathematical function such as logarithms?

27. How is re-expressing data helpful with regard to the spread across different groups?

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