Time Series Analysis Short Type Questions and Answers | Time Series Analysis MCQs Quiz

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Questions
1 Which of the following is not a necessary condition for weakly stationary time series?
A Mean is constant and does not depend on time
B Autocovariance function depends on s and t only through their difference |s-t| (where t and s are moments in time)
C The time series under considerations is a finite variance process
D Time series is Gaussian

Answer:Time series is Gaussian
2 Which of the following is not a technique used in smoothing time series?
A Nearest Neighbour Regression
B Locally weighted scatter plot smoothing
C Tree based models like (CART)
D Smoothing Splines

Answer:Tree based models like (CART)
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3 If the demand is 100 during October 2016, 200 in November 2016, 300 in December 2016, 400 in January 2017. What is the 3-month simple moving average for February 2017?
A 300
B 350
C 400
D Need more information

Answer:300
4 Suppose, you are a data scientist at Analytics Vidhya. And you observed the views on the articles increases during the month of Jan-Mar. Whereas the views during Nov-Dec decreases.

Does the above statement represent seasonality?

A TRUE
B FALSE
C Can’t Say

Answer:TRUE
5 Which of the following graph can be used to detect seasonality in time series data?

1. Multiple box

2. Autocorrelation

A Only 1
B Only 2
C 1 and 2
D None of these

Answer:1 and 2
6 Stationarity is a desirable property for a time series process.
A TRUE
B FALSE

Answer:TRUE
7 Imagine, you are working on a time series dataset. Your manager has asked you to build a highly accurate model. You started to build two types of models which are given below.

Model 1: Decision Tree model

Model 2: Time series regression model

At the end of evaluation of these two models, you found that model 2 is better than model 1. What could be the possible reason for your inference?

A Model 1 couldn’t map the linear relationship as good as Model 2
B Model 1 will always be better than Model 2
C You can’t compare decision tree with time series regression
D None of these

Answer:Model 1 couldn’t map the linear relationship as good as Model 2
8 Consider the following set of data:

{23.32 32.33 32.88 28.98 33.16 26.33 29.88 32.69 18.98 21.23 26.66 29.89}

What is the lag-one sample autocorrelation of the time series?

A 0.26
B 0.52
C 0.13
D 0.07

Answer:0.13
9 Any stationary time series can be approximately the random superposition of sines and cosines oscillating at various frequencies.
A TRUE
B FALSE

Answer: TRUE
10 Two time series are jointly stationary if _____ ?
A They are each stationary
B Cross variance function is a function only of lag h
C Only A
D Both A and B

Answer:Both A and B

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