Final study guide

13. When working with data sets in Excel, _____ can be used to automatically highlight cells that meet specified requirements. a. averaging b. conditional formatting c. summing d. sorting

b

11. Which one of the following is used in predictive analytics? a. Data dashboard b. Linear regression c. Data visualization d. Optimization model

b

43. A data _____ is a request to obtain information with certain characteristics from a database.

query

51. Veracity has to do with how much _____is in the data.

uncertainty

47. Predictive and prescriptive analytics can also be referred to as _____.

advanced analytics

1. A quantity of interest that can take on different values is known as a(n) _____. a. variable b. parameter c. sample d. observation

a

23. The _____ is a point estimate of the population mean for the variable of interest. a. sample mean b. median c. sample d. geometric mean

a

23. Utility theory is the study of the _____ or relative desirability of a particular outcome that reflects the decision maker's attitude toward a collection of factors, such as profit, loss, and risk. a. total worth b. total cost c. feasibility d. financial wellness

a

25. _____ refers to a programming model used within Hadoop that performs the two major steps for which it is named. the map step and the reduce step. a. MapReduce b. Internet of Things (IoT) c. Advanced analytics d. Optimization model

a

27. _____ analytics are techniques that use models, constructed from past data, to predict the future or to ascertain the impact of one variable on another. a. Predictive b. Descriptive c. Simulation d. Prescriptive

a

29. A _____ decision is concerned with how the organization should achieve the goals and objectives set by its strategy. a. tactical b. strategic c. intuitive d. operational

a

37. Any data value with a z-score less than -3 or greater than +3 is considered to be a(n) _____. a. outlier b. statistic c. whisker d. z-score value

a

5. The act of collecting data that are representative of the population data is called _____. a. random sampling b. sample data c. population sampling d. sources of data

a

63. A manager of a fast food restaurant wants the drive-thru employee to ask every fifth customer if he or she is satisfied with the service. Who makes up the population? a. All customers who use the drive-thru window of this fast food restaurant b. All survey respondents c. All customers of this restaurant d. The proportion of customers who say they are satisfied with their service

a

65. Which of the following relationships would have a negative correlation coefficient? a. Supply and demand b. Amount of a bill at a restaurant and the amount of the tip c. Cost of a car and the amount of tax to be paid d. The square footage of a home and the price of the home

a

In a survey of patients in a local hospital, 62.42% of the respondents indicated that the health care providers needed to spend more time with each patient. Who makes up the population? a. All patients in a local hospital b. All survey respondents c. Hospital patients d. Cannot be determined from the information given

a

these are called _____. a. legitimately missing data b. data cleansing c. illegitimate missing data d. missing random data

a

15. Simulation optimization helps _____. a. in identifying the constraints of the situation b. to find good decisions in highly complex and highly uncertain settings c. in assigning values to outcomes d. to model certainty using optimization techniques

b

17. _____ assigns values to outcomes based on the decision maker's attitude toward risk, loss, and other factors. a. Simulation optimization b. Utility theory c. Optimization model d. Data dashboard

b

21. In the financial sector, _____ are used to construct financial instruments such as derivatives. a. descriptive and prescriptive models b. predictive models c. descriptive models d. prescriptive models

b

25. Compute the median of the following data. 32, 41, 36, 24, 29, 30, 40, 22, 25, 37 a. 28 b. 31 c. 40 d. 34

b

3. The difference in a variable measured over observations (time, customers, items, etc.) is known as _____. a. observed differences b. variation c. variable change d. descriptive analytics

b

33. A better understanding of consumer behavior through analytics directly leads to _____. a. more profits b. better pricing strategies c. reduced advertising costs d. reduced risk

b

39. If the covariance between two variables is near 0, it implies that ______. a. a positive relationship exists between the variables b. the variables are not linearly related c. the variables are negatively related d. the variables are strongly related

b

7. Data dashboards are a type of _____analytics. a. predictive b. descriptive c. prescriptive d. decision

b

9. Data collected from several entities over a period of time (minutes, hours, days, etc.) are called _____. a. categorical and quantitative data b. time series data c. source data d. cross-sectional data

b

A _____ determines how far a particular value is from the mean relative to the data set's standard deviation. a. coefficient of variation b. z-score c. variance d. percentile

b

1. The decisions concerning an organization's goals and future plans are called _____. a. financial decisions b. tactical decisions c. strategic decisions d. operational decisions

c

15. Which of the following gives the proportion of items in each bin? a. Frequency b. Class size c. Relative frequency d. Bin proportion

c

19. The goal regarding using an appropriate number of bins is to show the _____. a. number of observations b. number of variables c. variation in the data d. correlation in the data

c

19. Which of the following sources of big data is not publicly available? a. Twitter b. Weather data c. Medical records d. Sports records

c

3. Picks and Axes Inc. is an Internet-based retail seller of hiking boots and mountaineering gear. The company decides to open retail stores across the major areas of the city to help complement its Internet-based strategy. This activity would be categorized as a(n) _____. a. tactical decision b. operational decision c. strategic decision d. financial decision

c

31. In the spectrum of business analytics, which is the most complex? a. Descriptive b. Predictive c. Prescriptive d. Operational

c

35. The U.S. Internal Revenue Service uses _____ to identify patterns that distinguish questionable annual personal income tax filings. a. utility theory b. prescriptive analytics c. data mining d. decision analysis

c

41. Scores on Ms. Bond's test have a mean of 70 and a standard deviation of 11. Michelle has a score of 48. Convert Michelle's score to a z-score. (Round to two decimal places if necessary.) a. 2 b. 41.64 c. -2 d. 1.33

c

9. Corporate-level managers use ______ to summarize sales by region, current inventory levels, and other company-wide metrics all in a single screen. a. simulations b. crosstabulation c. data dashboards d. tables

c

11. The data collected from the customers in restaurants about the quality of food is an example of a(n) _____. a. variable study b. cross-sectional study c. experimental study d. observational study

d

13. _____ are used in the pharmaceutical industry to assess the risk of introducing a new drug. a. Data dashboards b. Charts c. Spreadsheet models d. Simulations

d

21. Identify the shape of the distribution in the figure below. a. Skewed left b. Symmetric c. Approximately bell shaped d. Skewed right

d

5. Which of the following is not an approach to making decisions? a. Tradition b. Rules of thumb c. Intuition d. Guess and check

d

7. The amount of time taken by each of 10 students in a class to complete an exam is an example of what type of data? a. Cannot be determined b. Categorical data c. Time series data d. Quantitative data

d

39. The use of analytical techniques for better understanding patterns and relationships that exist in large data sets is ____

data mining

41. A decision concerned with how the organization is run from day to day is known as a(n) _____.

operational decision

45. A data _____ is trained in both computer science and statistics and knows how to effectively process and analyze large amounts of data.

scientist

37. An increase in data _____ would help to protect stored data from destructive forces or unauthorized users.

security

49. One of the 4 Vs of big data that refers to uncertainty due to data inconsistency and incompleteness, ambiguities, latency, deception, and model approximations is _____.

veracity

52. What are the four V's of big data?

volume, variety, velocity and veracity