Stats Chapter 1

Pataasin ang iyong marka sa homework at exams ngayon gamit ang Quizwiz!

26. Temperature is an example of a. a categorical variable. b. a quantitative variable. c. either a quantitative or categorical variable. d. neither a quantitative nor categorical variable.

b. a quantitative variable

6. Some hotels ask their guests to rate the hotel's services as excellent, very good, good, and poor. This is an example of the a. ordinal scale. b. ratio scale. c. nominal scale. d. interval scale.

a. ordinal scale

30. Data collected at the same, or approximately the same point in time are a. time series data. b. approximate time series data. c. cross-sectional data. d. approximate data.

c. cross-sectional data

18. All the data collected in a particular study are referred to as the a. inference. b. variable. c. data set. d. population.

c. data set

2. The process of capturing, storing, and maintaining data is known as a. data manipulation. b. data mining. c. data warehousing. d. big data.

c. data warehousing

1. Different methods of developing useful information from large data bases are dealt with under a. data manipulation. b. data warehousing. c. big data. d. data mining.

D. data mining

27. For ease of data entry into a university database, 1 denotes that the student is an undergraduate and 2 indicates that the student is a graduate student. In this case data are a. categorical. b. quantitative. c. either categorical or quantitative. d. neither categorical nor quantitative.

a. categorical

28. Arithmetic operations are inappropriate for a. categorical data. b. quantitative data. c. both categorical and quantitative data. d. large data sets.

a. categorical data

20. In a questionnaire, respondents are asked to mark their gender as male or female. Gender is an example of a(n) a. categorical variable. b. quantitative variable. c. interval-scale variable. d. ordinal-scale variable.

a. categorical variable

15. The entities on which data are collected are a. elements. b. populations. c. samples. d. observations.

a. elements

33. Statistical studies in which researchers control variables of interest are a. experimental studies. b. control observational studies. c. non-experimental studies. d. observational studies.

a. experimental studies

The subject of data mining deals with a. methods for developing useful decision-making information from large data bases. b. keeping data secure so that unauthorized individuals cannot access the data. c. computational procedure for data analysis. d. computing the average for data

a. methods for developing useful decision making information from large data.

10. Income is an example of a variable that uses the a. ratio scale. b. interval scale. c. nominal scale. d. ordinal scale.

a. ratio scale

12. The scale of measurement that has an inherent zero value defined is the a. ratio scale. b. nominal scale. c. ordinal scale. d. interval scale.

a. ratio scale

36. The collection of all elements of interest in a particular study is a. the population. b. the sample. c. statistical inference. d. descriptive statistics.

a. the population

31. Data collected over several time periods are a. time series data. b. time controlled data. c. cross-sectional data. d. categorical data.

a. time series data

11. Data measured a nominal scale a. must be alphabetic. b. can be either numeric or nonnumeric. c. must be numeric. d. must rank order the da

b. can be either numeric or nonnumeric

34. The summaries of data, which may be tabular, graphical, or numerical, are referred to as a. inferential statistics. b. descriptive statistics. c. statistical inference. d. data analytics.

b. descriptive statistics

4. In a questionnaire, respondents are asked to mark their gender as male or female. The scale of measurement for gender is a. ordinal scale. b. nominal scale. c. ratio scale. d. interval scale.

b. nominal scale

21. The number of observations will always be the same as the a. number of variables. b. number of elements. c. population size. d. sample size.

b. number of elements

16. The set of measurements collected for a particular element are called a. variables. b. observations. c. samples. d. populations.

b. observations

24. Ordinary arithmetic operations are meaningful a. only with categorical data. b. only with quantitative data. c. either with quantitative or categorical data. d. with neither quantitative or categorical data.

b. only with quantitative data

5. The scale of measurement that is used to rank order the observation for a variable is called the a. ratio scale. b. ordinal scale. c. nominal scale. d. interval scale.

b. ordinal scale

40. Five hundred residents of a city are polled to obtain information on voting intentions in an upcoming city election. The five hundred residents in this study is an example of a(n) a. census. b. sample. c. observation. d. population.

b. sample

8. Temperature is an example of a variable that uses a. the ratio scale. b. the interval scale. c. the ordinal scale. d. either the ratio or the ordinal scale

b. the interval scale

19. Quantitative data a. are always non-numeric. b. may be either numeric or non-numeric. c. are always numeric. d. are never numeric.

c. are always numeric

23. Categorical data a. indicate either how much or how many. b. cannot be numeric c. are labels used to identify attributes of elements. d. must be nonnumeric.

c. are labels used to identify attributes of elements

9. Arithmetic operations provide meaningful results for variables that a. use any scale of measurement except nominal. b. appear as non-numerical values. c. are quantitative. d. have non-negative values.

c. are quantitative

14. Data a. are always numeric. b. are always non-numeric. c. are the raw material of statistics. d. are always categorical.

c. are the raw material of statistics

13. The measurement scale suitable for quantitative data is a. ordinal scale. b. nominal scale. c. either interval or ratio scale. d. only interval scale

c. either interval or ratio scale

35. Statistical inference a. refers to the process of drawing inferences about the sample based on the characteristics of the population. b. is the same as descriptive statistics. c. is the process of drawing inferences about the population based on the information taken from the sample. d. is the same as a census.

c. is the process of drawing inferences about the population based on the information taken from the sample.

7. The data measured on ordinal scale exhibits all the properties of data measured on a. ratio scale. b. interval scale. c. nominal scale. d. nominal and interval scales.

c. nominal scale

39. In a sample of 400 students in a university, 80 or 20% are Business majors. Based on the above information, the school's paper reported that "20% of all the students at the university are Business majors." This report is an example of a. a sample. b. a population. c. statistical inference. d. descriptive statistics.

c. statistical inference

17. A characteristic of interest for the elements is called a a. sample. b. data set. c. variable. d. quality.

c. variable

25. Social security numbers consist of numeric values. Therefore, social security number is an example of a. a quantitative variable. b. either a quantitative or a categorical variable. c. an exchange variable. d. a categorical variable.

d. a categorical variable

37. A portion of the population selected to represent the population is called a. statistical inference. b. descriptive statistics. c. a census. d. a sample.

d. a sample

38. In a sample of 800 students in a university, 240 or 30% are Business majors. The 30% is an example of a. a sample. b. a population. c. statistical inference. d. descriptive statistics.

d. descriptive statistics

22. Categorical data a. must be numeric. b. must be nonnumeric. c. cannot be numeric. d. may be either numeric or nonnumeric.

d. may be either numeric or nonnumeric

32. Statistical studies in which researchers do not control variables of interest are a. experimental studies. b. uncontrolled experimental studies. c. not of any value. d. observational studies.

d. observational studies

29. Income is an example of a. categorical data. b. either categorical or quantitative data. c. nominal data. d. quantitative data.

d. quantitative data


Kaugnay na mga set ng pag-aaral

Chapter 10 (Strategic Decision-Making)

View Set

4.2 Government Regulation of Econ

View Set

Statistics of the Social Sciences Final Exam

View Set

Honan Chapter 30: Nursing Management: Diabetes Mellitus

View Set

MGMT 391 Organizational Behavior FINAL EXAM

View Set

Chapter 11: Design Patterns for SaaS Apps

View Set