Vol. 1 LM2 Data Types

Question 1

Concept

are data that can be measured or counted quantities as a number

p. 61

Answer 1

numerical data
OR
quantitative data

Question 2

Describe

numerical data

p. 61

Answer 2

are data that can be measured or counted quantities as a number

Question 3

Concept

are data that can be measured and can take on any numerical value in a specified range of values

Answer 3

continuous data

Question 4

Describe

continuous data

p. 61

Answer 4

are data that can be measured and can take on any numerical value in a specified range of values

Question 5

Concept

are numerical values that result from a counting process.

p. 61

Answer 5

discrete data

Question 6

Describe

discrete data

p. 61

Answer 6

are numerical values that result from a counting process.

Question 7

Concept

are categorical values that are not amenable to being organized in a logical order

p. 61

Answer 7

nominal data

Question 8

Describe

nominal data

p. 61

Answer 8

are categorical values that are not amenable to being organized in a logical order

Question 9

Concept

are categorical values that can be logically ordered or ranked

p. 62

Answer 9

ordinal data

Question 10

identify data type

Cash dividends per share paid by a public company. Note that cash divi- dends are a distribution paid to shareholders based on the number of shares owned.

p. 63

Answer 10

Cash dividends per share are continuous data since they can take on any non-negative values.

Question 11

Identify data type

Credit ratings for corporate bond issues. As background, credit ratings gauge the bond issuer’s ability to meet the promised payments on the bond. Bond rating agencies typically assign bond issues to discrete categories
that are in descending order of credit quality (i.e., increasing probability of non-payment or default).

p. 63

Answer 11

credit ratings are ordinal data

Question 12

Identify data type

Hedge fund classification types. Note that hedge funds are investment ve- hicles that are relatively unconstrained in their use of debt, derivatives, and long and short investment strategies. Hedge fund classification types group hedge funds by the kind of investment strategy they pursue.

p. 63

Answer 12

Hedge fund classification types are nominal data. Each type groups together hedge funds with similar investment strategies. In contrast to credit ratings for bonds, however, hedge fund classification schemes do not involve a ranking. Thus, such classification schemes are not ordinal data.

Question 13

Another data classification standard is based on how data are collected, and it cate- gorizes data into three types

p. 63

Answer 13

1. cross-sectional data
2. time series data
3. panel data

Question 14

Concept

is a characteristic or quantity that can be measured, counted, or categorized and is subject to change.

p. 63

Answer 14

variable

Question 15

Describe

variable

p. 63

Answer 15

is a characteristic or quantity that can be measured, counted, or categorized and is subject to change

Question 16

Concept

are a sequence of observations for a single observational unit of a specific variable collected over time and at discrete and typically equally spaced intervals of time

p. 64

Answer 16

time-series data

Question 17

Describe

time-series data

p. 64

Answer 17

are a sequence of observations for a single observational unit of a specific variable collected over time and at discrete and typically equally spaced intervals of time

Question 18

Concept

are a list of observations a specific variable from multiple observational units

p. 64

Answer 18

cross-sectional data

Question 19

Describe

cross-sectional data

p. 64

Answer 19

are a list of observations a specific variable from multiple observational units

Question 20

Concept

• are a mix of time-series and cross-sectional data that are frequently used in financial analysis and modeling.
• These data consist of observations through time on one or more variables for multiple observational units

p. 64

Answer 20

panel data

Question 21

Concept

the observational data in this data type are usually organized in a matrix format called a data table

p. 64

Answer 21

panel data

Question 22

Concept

are highly organized in a pre-defined manner, usually with repeating patterns

p. 64

Answer 22

structured data

Question 23

Describe

structured data

p. 64

Answer 23

are highly organized in a pre-defined manner, usually with repeating patterns

Question 24

Concept

typical format of this type of data is a one-dimensional array or a two-dimensional table or matrix

p. 64

Answer 24

structured data

Question 25

# Concept are data that do not follow any conventionally organized forms, such as financial news or company filings. ## Footnote p. 65

Answer 25

**unstructured data**

Question 26

# Describe **unstructured data** ## Footnote p. 65

Answer 26

* are data that do not follow any conventionally organized forms * DAGs are format for dealing with unstructured data * JSONs for semi-structured data

Question 27

1. Which of the following is most likely to be structured data? A. Social media posts where consumers are commenting on what they think of a company’s new product. B. Daily closing prices during the past month for all companies listed on Japan’s Nikkei 225 stock index. C. Audio and video of a CFO explaining her company’s latest earnings announcement to securities analysts. ## Footnote p. 67

Answer 27

B. Daily closing prices represent structured time-series data

Question 28

Which of the following statements describing panel data is most accurate? A. It is a sequence of observations for a single observational unit of a specific variable collected over time at discrete and equally spaced intervals. B. It is a list of observations of a specific variable from multiple observational units at a given point in time. C. It is a mix of time-series and cross-sectional data that are frequently used in financial analysis and modeling. ## Footnote p. 67

Answer 28

C. it is a mix of time-series and cross-sectional data

Question 29

Which of the following data series is least likely to be sortable by values? A. Daily trading volumes for stocks listed on the Shanghai Stock Exchange. B. EPS for a given year for technology companies included in the S&P 500 Index. C. Dates of first default on bond payments for a group of bankrupt European manufacturing companies.

Answer 29

C. dates are ordinal data that can be sorted by chronological order, but not by value

Question 30

Which of the following best describes a time series? A. Daily stock prices of the XYZ stock over a 60-month period. B. Returns on four-star rated Morningstar investment funds at the end of the most recent month. C. Stock prices for all stocks in the FTSE100 on 31 December of the most recent calendar year. ## Footnote p. 67

Answer 30

A. a time series is a sequence of observations of a speicific variable collected over time (60 months)

Question 31

# Concept data available in their original format, typically unusable by humans or computers ## Footnote p. 67

Answer 31

**raw data**

Question 32

# Concept the simplest format for representing a collection of data of the same data type, which is suitable for a single variable ## Footnote p. 68

Answer 32

**one-dimensional array** ex. vectors

Question 33

# Concept summarizes central tendency and spread variation in the data's distribution ## Footnote p. 68

Answer 33

**descriptive statistics**

Question 34

# Describe **descriptive statistics** ## Footnote p. 68

Answer 34

summarizes central tendency and spread variation in the data's distribution

Question 35

# Concept is a tabular display of data constructed either by counting the observations of a variable by dinstict values or groups or by tallying the values ## Footnote p. 71

Answer 35

**frequency distribution**

Question 36

# steps Constructing a frequency distribution of a categorical variable ## Footnote p. 71

Answer 36

1. count the number of observations for each unique value of the variable 2. construct a table listing each unique value and the corresponding counts, and then sort the records

Question 37

# Concept the raw frequency that is the actual number of observations counted for each unique value ## Footnote p. 71

Answer 37

**absolute frequency**

Question 38

# Describe **absolute frequency**

Answer 38

the raw frequency that is the actual number of observations counted for each unique value

Question 39

# Concept is calculated as the absolute frequency of each unique value of the variable divided by the total number of observations

Answer 39

**relative frequency**

Question 40

# Describe **relative frequency**

Answer 40

is calculated as the absolute frequency of each unique value of the variable divided by the total number of observations

Question 41

# pitfalls binning data and constructing intervals ## Footnote p. 74

Answer 41

* if we use too few bins, we wil summarize too much and may lose pertinent characteristics * if we use too many bins, we may not summarize enough, and potentially introduce noise into the data

Question 42

# Concept adds up the absolute frequencies as we move from the first bin to the last bin ## Footnote p. 74

Answer 42

**cumulative absolute frequency**

Question 43

# Describe **cumulative absolute frequency** ## Footnote p. 74

Answer 43

* adds up the absolute frequencies as we move from the first bin to the last bin * for the last bin, the cumulative absolute frequency will equal the number of observations in the dataset

Question 44

# Concept is a sequence of partial sums of the relative frequencies ## Footnote p. 74

Answer 44

**cumulative relative frequency**

Question 45

**cumulative relative frequency**

Answer 45

is a sequence of partial sums of the relative frequencies

Question 46

# Concept is a tabular format that displays the frequency distributions of two or more categorical variables simulatneously and is used for finding patterns between the variables ## Footnote p. 77

Answer 46

**contingency table**

Question 47

# Concept a **contingency table** for two categorical variables ## Footnote p. 77

Answer 47

two-way table

Question 48

# Concept A **contingency table** having *R* levels of one variable in rows and *C* levels of the other variable in columns ## Footnote p. 77

Answer 48

*R* x *C* table

Question 49

# name the data representation ## Footnote p. 78

Answer 49

*5* x *3* contingency table

Question 50

# Name the data type ## Footnote p. 78

Answer 50

**joint frequencies**

Question 51

# Name the data type ## Footnote p. 78

Answer 51

**marginal frequencies**

Question 52

# Name the table ## Footnote p. 80

Answer 52

**Confusion Matrix** for Bond Default Prediction Model

Question 53

# Describe **chi-square test of independence** ## Footnote p. 80

Answer 53

* A way to test for a potential association between categorical variables * the procedure involves constructing a **contingency table** * the actual values and expected values are used to derive the chi-square test statistic

Question 54

# Concept the actual values and expected values from a contingency table are used to derive this value ## Footnote p. 80

Answer 54

chi-square test statistic

Question 55

Describe how the contingency table is used to set up a test for independence between fund style and risk level. ## Footnote p. 81

Answer 55