Reference no: EM13927492
Chapter 1
1. An example of a quantitative variable is the telephone number of an individual.
2. If we examine some of the population measurements, we are conducting a Sample of the population.
3. An example of a nominal scale variable is the make of a car.
4. Credit score is an example of a ratio scale variable.
5. Temperature is an example of an interval scale variable.
6. The number of people eating at a local café between noon and 2:00 p.m. is an example of a discrete variable.
Chapter2
7. The relative frequency for a class is the frequency of the class divided by the number of classes.
8. When we wish to summarize the proportion (or fraction) of items in a class we use the relative frequency for that class.
9. When establishing the classes for a frequency table it is generally agreed that the more classes you use the better your frequency table will be. FALSE We try to follow the 2k rule. Having too many classes is not good.
10. The cumulative distribution function is initially increasing then decreasing.
11. A Histogram is a graphic that is used to depict qualitative data. FALSE Bar Chart is used for qualitative data.
Chapter 3
12. The Median is the measure of central tendency that divides a population or sample into two equal parts.
13. If there are 7 classes in a frequency distribution then the fourth class necessarily contains the median.
14. The sum of deviations from the mean must be zero.
15. The median is said to be less sensitive to extreme values. TRUE This statement is a relative statement (implicitly) comparing Median with the other popular measure of central tendency, namely, the Mean. But some students read the statement in absolute terms and answered it wrong although they knew that Median is not sensitive to extreme values. Therefore, I removed this question from grading.
16. The Empirical Rule is used to describe a population that is highly skewed. FALSE It is based on the symmetrical Normal distribution and can be safely applied only for slightly skewed non-Normal distributions. For highly skewed distribution it is not appropriate.
Multiple Choices (each question carries three points):
Chapter 1
1. Ratio variables have the following unique characteristic:
A. Meaningful order
B. An inherently defined zero value
C. Categorical in nature
D. Predictable
2. Which of the following is a quantitative variable?
A. The make of a TV
B. The VIN of a car
C. The price of a TV
D. The rank of a police officer
E. The Driver's License Number
3. Which of the following is a categorical or Nominal variable?
A. Air Temperature
B. Bank Account Balance
C. Daily Sales in a Store
D. The Social Security Number of a person
E. Value of Company Stock
4. Which of the following is not a typical use of inferential statistics?
A. Develop forecasts
B. Summarize data
C. Estimate relationships
D. Test assumptions
5. The level of Satisfaction in a Consumer survey would represent a(n) ____________ level of measurement.
A. Nominative
B. Ordinal
C. Interval
D. Ratio
Chapter 2
6. A(n) ______ is a graph of a cumulative distribution.
A. Histogram
B. Bar Chart
C. Ogive plot
D. Pie Chart
7. When developing a frequency distribution the class (group), intervals must be
A. Large
B. Small
C. Whole numbers
D. Mutually exclusive
E. Equal
Although having equal intervals (or nearly equal intervals) is generally desirable, it is not necessary and not even appropriate in some applications. For example, in Income distribution the classes are arbitrarily formed and are generally unequal. Similarly many distributions have the lowest and/or highest class with open bounds which make these class intervals different from other classes.
8. If there are 60 values in a data set, how many classes should be created for a frequency histogram?
A. 4
B. 5
C. 6
D. 7
E. 8
Just apply the 2k rule for question 8.
9. Consider the following frequency distribution from Excel. What is the missing value?
Bin Frequency Cumulative %
584 1 4.00%
1774.4 64.00%
2964.8 4 80.00%
4155.2 3 92.00%
5345.6 1 96.00%
More 1 100.00%
A. 3
B. 10
C. 15
D. 16
E. 25
10. A company collected the ages from a random sample of its middle managers with the resulting frequency distribution shown below:
Class Interval Frequency
20 to 25 8
25 to 30 12
30 to 35 28
35 to 40 20
40 to 45 6
45 to 50 6
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