, Principles of Data Science
Chapter 5
Time Series and Forecasting
Critical Thinking
[5.1, LO 5.1.1, 5.1.2]
1.
a. What characteristics define a time series?
b. Which of the following are examples of time series data?
i. The vital statistics of a cancer patient taken right before a major surgery
ii. The monthly expenses of a small company recorded over a period of five years
iii. Daily temperature, rainfall, humidity, and wind speeds measured at a particular
location over a few months
iv. Student final grades in all sections of a course at a university
Solution a: A time series consists of data that are observed or recorded at regular time intervals
and ordered sequentially.
Solution b: ii and iii.
Option i is not a time series since the vital statistics were recorded at a single point in time.
Option ii is a time series because expenses are recorded at regular time intervals (monthly) in a
sequence. Option iii is a time series because data are collected daily over a period of time. (In
fact, each measurement—temperature, rainfall, humidity, and wind speed—constitutes a
separate time series.) Option iv is not a time series because the grade data are collected at a
single point in time.
[5.2, LO 5.2.3]
3.
a. What are the characteristics of white noise? Why is it important that the residuals of a
time series model be white noise?
b. Determine which of the following graphs most likely represents white noise.
11/11/24 For more free, peer-reviewed, openly licensed resources visit OpenStax.org. 2
Chapter 5
Time Series and Forecasting
Critical Thinking
[5.1, LO 5.1.1, 5.1.2]
1.
a. What characteristics define a time series?
b. Which of the following are examples of time series data?
i. The vital statistics of a cancer patient taken right before a major surgery
ii. The monthly expenses of a small company recorded over a period of five years
iii. Daily temperature, rainfall, humidity, and wind speeds measured at a particular
location over a few months
iv. Student final grades in all sections of a course at a university
Solution a: A time series consists of data that are observed or recorded at regular time intervals
and ordered sequentially.
Solution b: ii and iii.
Option i is not a time series since the vital statistics were recorded at a single point in time.
Option ii is a time series because expenses are recorded at regular time intervals (monthly) in a
sequence. Option iii is a time series because data are collected daily over a period of time. (In
fact, each measurement—temperature, rainfall, humidity, and wind speed—constitutes a
separate time series.) Option iv is not a time series because the grade data are collected at a
single point in time.
[5.2, LO 5.2.3]
3.
a. What are the characteristics of white noise? Why is it important that the residuals of a
time series model be white noise?
b. Determine which of the following graphs most likely represents white noise.
11/11/24 For more free, peer-reviewed, openly licensed resources visit OpenStax.org. 2
