ch11. A population is a set of existing units.   

True    False 2. If we examine some of the population measurements, we are conducting a census of the population.   

True    False 3. A random sample is selected so that every element in the population has the same chance of being

included in the sample.   True    False

 4. An example of a quantitative variable is the make of a car.   

True    False 5. An example of a qualitative variable is the mileage of a car.   

True    False 6. Statistical inference is the science of using a sample of measurements to make generalization about the

important aspects of a population of measurements.   True    False

 7. Time series data are data collected at the same time period.   

True    False 8. Cross-sectional data are data collected at the same point in time.   

True    False 9. Daily temperature in a local community collected over a 30-day time period is an example of cross-

sectional data.   True    False

 10. The number of sick days taken by employees in 2008 for the top 10 technology companies is an example

of time-series data.   True    False

 11. The number of sick days per month taken by employees for the last ten years at Apex Co. is an example

of time-series data.   True    False

 12. A quantitative variable can also be referred to as a categorical variable.   

True    False 13. In a data set of information on college business students, an example of an element is their cumulative

gpa.   True    False

 14. In an observational study, the variable of interest is called a response variable.   

True    False 15. In an experimental study, the aim is to manipulate or set the value of the response variable.   

True    False 16. The science of describing the important aspects of a set of measures is called statistical inference.   

True    False 17. A practical method of selecting a random sample is to utilize a random number table.   

True    False 

18. It is possible to use a random sample from one population to make statistical inferences about another related population.   True    False

 19. Processes produce outputs over time.   

True    False 20. Ratio variables have the following characteristics:   

A. Meaningful orderB. An inherently defined zero valueC. Categorical in natureD. Predictable

 21. Which of the following is a quantitative variable?   

A. The make of a TVB. A person's genderC. Mileage of a carD. Whether a person is a college graduateE. Whether a person has a charge account

 22. Which of the following is a categorical variable?   

A. Air TemperatureB. Bank Account BalanceC. Daily Sales in a StoreD. Whether a Person Has a Traffic ViolationE. Value of Company Stock

 23. Measurements from a population are called   

A. ElementsB. ObservationsC. VariablesD. Processes

 24. The two types of quantitative variables are:   

A. Ordinal and ratioB.  Interval and ordinalC. Nominative and ordinalD.  Interval and ratioE. Nominative and interval

 25. Temperature (in degrees Fahrenheit) is an example of a(n) ________ variable.   

A. NominativeB. OrdinalC.  IntervalD. Ratio

 26. Jersey numbers of soccer players is an example of a(n) ___________ variable.   

A. NominativeB. OrdinalC.  IntervalD. Ratio

 27. The weight of a chemical compound used in an experiment that is obtained using a well-adjusted scale

represents a(n) _____________ level of measurement.   A. NominativeB. OrdinalC.  IntervalD. Ratio

 

28. An identification of police officers by rank would represent a(n) ____________ level of measurement.   A. NominativeB. OrdinalC.  IntervalD. Ratio

 29. __________ is a necessary component of a runs plot.   

A. Observation over timeB. Qualitative variableC. Random sampling of the dataD. Cross sectional data

 30. ______________ is the science of using a sample to make generalizations about the important aspects of

a population.   A. Time Series AnalysisB. Descriptive StatisticsC. Random sampleD. Statistical Inference

 31. College entrance exam scores, such as SAT scores, are an example of a(n) ________________

variable.   A. OrdinalB. RatioC. NominativeD.  Interval

 32. The number of miles a truck is driven before it is overhauled is an example of a(n) _____________

variable.   A. NominativeB. OrdinalC.  IntervalD. Ratio

 33. A(n) ___________________ variable is a qualitative variable such that there is no meaningful ordering or

ranking of the categories.   A. RatioB. OrdinalC. NominativeD.  Interval

 34. A person's telephone area code is an example of a(n) _____________ variable.   

A. NominativeB. OrdinalC.  IntervalD. Ratio

 35. Any characteristic of a population unit is a(n):   

A. MeasurementB. SampleC. ObservationD. Variable

 36. Examining all population measurements is called a ____.   

A. CensusB. FrameC. SampleD. Variable

 

37. Any characteristic of an element is called a ____.   A. SetB. ProcessC. VariableD. Census

 38. The process of assigning a value of a variable to each element in a data set is called ____.   

A. SamplingB. MeasurementC. Experimental analysisD. Observational analysis

 39. A ____ is a display of individual measurements versus time.   

A. Runs plotB. Statistical analysisC. Random sampleD. Measurement

 40. Statistical _____ refers to using a sample of measurements making generalizations about the important

aspects of a population.   A. SamplingB. ProcessC. AnalysisD.  Inference

 41. A _____ is a subset of the units in a population.   

A. CensusB. FrameC. SampleD. Variable

 42. A _____ variable can have values that are numbers on the real number line.   

A. QualitativeB. QuantitativeC. CategoricalD. Nominative

 43. A sequence of operations that takes inputs and turns them into outputs is a ____.   

A. ProcessB. Statistical analysisC. Runs plotD. Random sampling

 44. A(n) _____ variable can have values that indicate into which of several categories of a population it

belongs.   A. QualitativeB. QuantitativeC. RatioD.  Interval

 45. A set of all elements we wish to study is called a ____.   

A. SampleB. FrameC. CensusD. Population

 

46. _____ refers to describing the important aspects of a set of measurements.   A. Cross Sectional analysisB. Runs plotC. Descriptive statisticsD. Times Series analysis

 47. A _____ is used to help select items for a random sample.   

A. Runs plotB. Qualitative variableC. Ratio variableD. Random number table

 48. The change in daily price of a stock is what type of variable?   

A. QualitativeB. OrdinalC. RandomD. Quantitative

 49. Data collected for a particular study are referred to as a data ______.   

A. VariableB. MeasurementC. SetD. Element

 50. A data set provides information about some group of individual _________.   

A. VariablesB. ElementsC. StatisticsD. Measurements

 51. When the source of the data being studied is gathered from a private source, this is referred to as a(n)

______________________.   A. Existing data sourceB. Observational data sourceC. Experimental data sourceD. Cross-sectional data source

 52. One method of determining whether a sample being studied can be used to make statistical inferences

about the population is to:   A. Run a descriptive statistical analysisB. Calculate a proportionC. Create a cross-sectional data analysisD. Produce a runs plot

 53. A study is being conducted on the effect of gas price on the number of miles driven in a given month.

Residents in two cities, one on the east coast and one on the west coast are randomly selected and asked to complete a questionnaire on the type of car they drive, the number of miles they live from work, the number of children under 18 in their household, their monthly income and the number of miles they have driven over the past 30 days. List the response variable(s).   

 

 

 

 

54. A study is being conducted on the effect of gas price on the number of miles driven in a given month. Residents in two cities, one on the east coast and one on the west coast are randomly selected and asked to complete a questionnaire on the type of car they drive, the number of miles they live from work, the number of children under 18 in their household, their monthly income and the number of miles they have driven over the past 30 days. Is this an experimental or observational study?   

 

 

 

 55. A study is being conducted on the effect of gas price on the number of miles driven in a given month.

Residents in two cities, one on the east coast and one on the west coast are randomly selected and asked to complete a questionnaire on the type of car they drive, the number of miles they live from work, the number of children under 18 in their household, their monthly income and the number of miles they have driven over the past 30 days. List the factor(s).   

 

 

 

 56. Looking at the runs plot of gasoline prices over the past 30 months describe what it tells us about the

price of gas during these 30 months.       

 

 

 

 

57. Using the following data table of the average hours per week spent on internet activities by 15-18 year

olds for the years 1999-2008, construct the runs plot and interpret.       

 

 

 

 

ch1 Key  1. TRUE 2. FALSE 3. TRUE 4. FALSE 5. FALSE 6. TRUE 7. FALSE 8. TRUE 9. FALSE 10. FALSE 11. TRUE 12. FALSE 13. FALSE 14. TRUE 15. FALSE 16. FALSE 17. TRUE 18. TRUE 19. TRUE 20. B 21. C 22. D 23. B 24. D 25. C 26. A 27. D 28. B 29. A 30. D 31. D 32. C 33. C 34. A 35. D 36. A 

37. C 38. B 39. A 40. D 41. C 42. B 43. A 44. A 45. D 46. C 47. D 48. D 49. C 50. B 51. A 52. D 53. Response variable in this study is the number of miles driven over the past 30 days. 54. Observational study 55. Factors in this study are type of car, number of miles from work, number of children under 18 and monthly income. 56. Price of gas peaked in the 7-8 month with the lowest price two years in from the start of the data collection and at the end of the 30 months is beginning to show stability. Interpretation: Hrs spent on the internet have increased over the past 8 years but shows a slight leveling off in the last 3 years.

57.    

 

ch1 Summary  Category # of Questions

AACSB: Reflective Thinking 57

Blooms: Comprehension 20

Blooms: Knowledge 37

Bowerman - Chapter 01 57

Difficulty: Easy 22

Difficulty: Hard 2

Difficulty: Medium 33

Learning Objective: 01-01 Explain what a variable is. 6

Learning Objective: 01-02 Describe the difference between a quantitative variable and a qualitative variable. 8

Learning Objective: 01-03 Describe the difference between crosssectional data and time series data. 5

Learning Objective: 01-04 Construct and interpret a time series (runs) plot. 5

Learning Objective: 01-05 Identify the different types of data sources: existing data sources; experimental studies; and observational studies.

6

Learning Objective: 01-06 Describe the difference between a population and a sample. 6

Learning Objective: 01-07 Distinguish between descriptive statistics and statistical inference. 5

Learning Objective: 01-08 Explain the importance of random sampling. 6

Learning Objective: 01-09 Identify the ratio; interval; ordinal; and nominative scales of measurement (Optional). 10

Topic: Cross-Sectional Data 2

Topic: Data 3

Topic: Data sources - Experimental study 1

Topic: Data sources - Observational study 1

Topic: Descriptive Statistics 1

Topic: Existing Data Source 1

Topic: Observational study 3

Topic: Population 7

Topic: Process 2

Topic: Process/Statistical Control 1

Topic: Quantitative 1

Topic: Random sampling 3

Topic: Sample 5

Topic: Statistical Inference 1

Topic: Time Series Data 6

Topic: Variable 19