TEST BANK FOR STATISTICS FOR BUSINESS AND ECONOMICS 10th Edition By James T. McClave P. George

Descriptive statistics utilizes numerical and graphical methods to look for patterns, to
summarize, and to present the information in a set of data. Inferential statistics utilizes sample
data to make estimates, decisions, predictions, or other generalizations about a larger set of
data.
1.4 The first element of inferential statistics is the population of interest. The population is a set of
existing units. The second element is one or more variables that are to be investigated. A
variable is a characteristic or property of an individual population unit. The third element is
the sample. A sample is a subset of the units of a population. The fourth element is the
inference about the population based on information contained in the sample. A statistical
inference is an estimate, prediction, or generalization about a population based on information
contained in a sample. The fifth and final element of inferential statistics is the measure of
reliability for the inference. The reliability of an inference is how confident one is that the
inference is correct.
1.6 Quantitative data are measurements that are recorded on a meaningful numerical scale.
Qualitative data are measurements that are not numerical in nature; they can only be classified
into one of a group of categories.
1.8 A population is a set of existing units such as people, objects, transactions, or events. A
sample is a subset of the units of a population.
1.10 An inference without a measure of reliability is nothing more than a guess. A measure of
reliability separates statistical inference from fortune telling or guessing. Reliability gives a
measure of how confident one is that the inference is correct.
1.12 Statistical thinking involves applying rational thought processes to critically assess data and
inferences made from the data. It involves not taking all data and inferences presented at face
value, but rather making sure the inferences and data are valid.
1.14 a. The two variables measured are ‘type of credit card used’ and ‘amount of purchase.’
‘Type of credit card used’ is qualitative. It has no meaningful number associated with it,
only the name of the card used. ‘Amount of purchase’ is quantitative. It has a meaningful
number associated with it.
b. In Study 1, it says that all purchases were tracked. Thus, the data represent a population.
1.16 a. High school GPA is a number usually between 0.0 and 4.0. Therefore, it is quantitative.
b. Honors/awards would have responses that name things. Therefore, it would be
qualitative.
Statistics, Data, and Statistical Thinking 1
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c. The scores on the SAT's are numbers between 200 and 800. Therefore, it is quantitative.
d. Gender is either male or female. Therefore, it is qualitative.
e. Parent's income is a number: $25,000, $45,000, etc. Therefore, it is quantitative.
f. Age is a number: 17, 18, etc. Therefore, it is quantitative.
1.18 a. 1. The variable of interest is the status of a company’s e-commerce strategy.
Since a company either has an e-commerce strategy or not, the variable is
qualitative.
2. The variable of interest is when the company will implement an e-commerce plan.
Since the time of implementation will be a date, this variable will be qualitative.
3. The variable of interest is whether the company is delivering products over the
internet or not. Since the company is either delivering products or not, the variable
is qualitative.
4. The variable of interest is the company’s total revenue in the last fiscal year. Since
this is a meaningful number, this variable is quantitative.
b. Since there are many more that 154 companies in the U.S., this represents a sample rather
than a population.
1.20 a. The population of interest is the collection of computer security personnel at all U.S.
corporations and government agencies.
b. Surveys were sent to computer security personnel at all U. S. corporations and
government agencies. However, in 2006, only 616 organizations responded to the
survey. There could be nonresponse bias. Often, only those subjects with strong
opinions will respond to a survey. Thus, the responses may not reflect what the
population as a whole thinks.
c. The variable measured in the survey is whether or not there was unauthorized use of
computer systems at the firms during the year. Since the responses will be either ‘Yes’
or “No’, the variable is qualitative.
d. If we assume that the responses were a random sample from the population, we could
infer that about 52% of all computer security personnel will admit to unauthorized use of
computer systems at their firms during the year.
1.22. a. The data collection method used is a designed experiment.
b. The experimental units in the study are the 50,000 smokers.
c. The variable of interest is the age at which the scanning method first detects a tumor.
Since this is a meaningful number, this variable is quantitative.
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