Statistics for Managers Using Microsoft Excel 9th Global Edition by David Levine Test bank
ANSWER:
a
TYPE: MC DIFFICULTY: Easy
KEYWORDS: variable
a
TYPE: MC DIFFICULTY: Easy
KEYWORDS: variable
- True or False: Problems may arise when statistically unsophisticated users who do not understand the assumptions behind the statistical procedures or their limitations are misled by results obtained from computer software.
True
TYPE: TF DIFFICULTY: Easy
KEYWORDS: statistical package
- True or False: Managers need an understanding of statistics to be able to present and describe information accurately, draw conclusions about large populations based on small samples, improve processes, and make reliable forecasts.
True
TYPE: TF DIFFICULTY: Easy
KEYWORDS: reasons for learning statistics
- True or False: A professor computed the sample average exam score of 20 students and used it to estimate the average exam score of the 1,500 students taking the exam. This is an example of inferential statistics.
True
TYPE: TF DIFFICULTY: Easy
KEYWORDS: descriptive statistics, inferential statistics
- True or False: Using the number of registered voters who turned out to vote for the primary in Iowa to predict the number of registered voters who will turn out to vote in Vermont’s primary is an example of descriptive statistics.
False
TYPE: TF DIFFICULTY: Easy
KEYWORDS: descriptive statistics, inferential statistics
- True or False: Compiling the number of registered voters who turned out to vote for the primary in Iowa is an example of descriptive statistics.
True
TYPE: TF DIFFICULTY: Easy
KEYWORDS: descriptive statistics, inferential statistics
- The Human Resources Director of a large corporation wishes to develop an employee benefit package and decides to select 500 employees from a list of all (N = 40,000)workers in order to study their preferences for the various components of a potential package. In this study, methods involving the collection, presentation, and characterization of the data are called .
descriptive statistics/methods TYPE: FI DIFFICULTY: Easy
KEYWORDS: descriptive statistics
- The Human Resources Director of a large corporation wishes to develop an employee benefit package and decides to select 500 employees from a list of all (N = 40,000)workers in order to study their preferences for the various components of a potential package. In this study, methods that result in decisions concerning population characteristics based only on the sample results are called .
inferential statistics/methods TYPE: FI DIFFICULTY: Easy
KEYWORDS: inferential statistics
- The oranges grown in corporate farms in an agricultural state were damaged by some unknown fungi a few years ago. Suppose the manager of a large farm wanted to study the impact of the fungi on the orange crops on a daily basis over a 6-week period. On each day a random sample of orange trees was selected from within a random sample of acres. The daily average number of damaged oranges per tree and the proportion of trees having damaged oranges were calculated. In this study, drawing conclusions on any one day about the true population characteristics based on information obtained from the sample is called .
inferential statistics/methods TYPE: FI DIFFICULTY: Moderate
KEYWORDS: inferential statistics
- The oranges grown in corporate farms in an agricultural state were damaged by some unknown fungi a few years ago. Suppose the manager of a large farm wanted to study the impact of the fungi on the orange crops on a daily basis over a 6-week period. On each day a random sample of orange trees was selected from within a random sample of acres. The daily average number of damaged oranges per tree and the proportion of trees having damaged oranges were calculated. In this study, the presentation and characterization of the two main measures calculated each day (i.e., average number of damaged oranges per tree and proportion of trees having damaged oranges) is called