Index Numbers and Time series 0 Index Numbers and Time series 1 / 26 Q.30 Secular trend can be measured by: Two methods Three methods Four methods Five methods 2 / 26 Q.29 A time series consists of: Short-term variations Long-term variations Irregular variations All of the above 3 / 26 Q.28 An orderly set of data arranged in accordance with their time of occurrence is called: Arithmetic series Harmonic series Geometric series Time series 4 / 26 Q.27 In a time-series forecasting problem, if the seasonal indices for quarters 1, 2, and 3 are 0.80, 0.90, and 0.95 respectively. What can you say about the seasonal index of quarter 4? It will be less than 1 It will be greater than 1 It will be equal to 1 Seasonality does not exist Data is insufficient 5 / 26 Q.26 Second differencing in time series can help to eliminate which trend? Quadratic Trend Linear Trend Both 1 & 2 None of the above 6 / 26 Q.25 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? TRUE FALSE Both None 7 / 26 Q.24 If the demand is 100 during October 2017, 200 in November 2017, 300 in December 2017, 400 in January 2018. What is the 3 - month simple moving average for February 2018? 300 350 400 Need more information 8 / 26 Q.23 Which of the following is not a technique used in smoothing time series? Nearest Neighbour Regression Locally weighted scatter plot smoothing Tree based models like (CART) Smoothing Splines 9 / 26 Q.22 Which of the following is not a necessary condition for weakly stationary time series? Mean is constant and does not depend on time Autocovariance function depends on s and t only through their difference |s - t| (where t and s are moments in time) The time series under considerations is a finite variance process Time series is Gaussian 10 / 26 Q.21 The last period's forecast was 70 and demand was 60. What is the simple exponential smoothing forecast with alpha of 0.4 for the next period. 63.8 65 62 66 11 / 26 Q.20 Sum of weights in exponential smoothing is _____. < 1 1 > 1 None of the above 12 / 26 Q.19 Smoothing parameter close to one gives more weight or influence to recent observations over the forecast. TRUE FALSE Both None 13 / 26 Q.18 Which of the following is relatively easier to estimate in time series modeling? Seasonality Cyclical No difference between Seasonality and Cyclical None of the above 14 / 26 Q.17 Which of the following cannot be a component for a Time Series Plot? Seasonality Trend Cyclical Noise None of the above 15 / 26 Q.16 Which of the following is not an example of a Time Series Model? Naive approach Exponential smoothing Moving Average None of the above 16 / 26 Q.15 Which of the following is an example of time series problem? (i) Estimating number of hotel rooms booking in next 6 months. (ii) Estimating the total sales in next 3 years of an insurance company. (iii) Estimating the number of calls for the next one week. Only 3 1 and 2 2 and 3 1 and 3 1, 2 and 3 17 / 26 Q.14 Out of 80 students in a class, 30 passed in Mathematics, 20 passed in Statistics and 10 passed in both. One student is selected at random. Find the probability that he has passed only in Maths. 03-Jan 05-Jan 1 2 1 4 18 / 26 Q.13 There are four hotels in a certain town. If 3 men check into hotels in a day, what is the probability that each check into a different hotels ? 08-Jul 08-Aug 08-Mar 06-Aug 19 / 26 Q.12 A die is so biased that it is twice as likely to show an even number as an odd number when thrown. It is thrown twice. What is the probability that sum of the two numbers shown is even ? 09-Apr 09-Mar 09-Feb 09-May 20 / 26 Q.11 An investment consultant predicts that the odds against the price of a certain stock going up are 2 : 1 and the odds in favour of the price remaining the same are 1 : 3. what is the probability that the price of the stock will go down ? 12-May 06-May 05-Dec 05-Jun 21 / 26 Q.10 P(A-B)=">P(A−B)= P ( A ) − P ( B ) P ( A ) + P ( A ∩ B ) P ( B ) − P ( A ∩ B ) P ( A ) − P ( A ∩ B ) 22 / 26 Q.9 If the prices of all the commodities in the current year has increased by 1.5 times compared to the base period price, then the price index no. for the current year is : 150 250 120 None of these 23 / 26 Q.8 Laspeyre, Paasche & Fishers method do not satisfies : Unit test Time reversal Factor reversal test Circular test 24 / 26 Q.7 Unit test is not satisfied by : Simple average of relative method Paasche's method Simple aggregative method Weighted average of relative method 25 / 26 Q.6 Index number depicts broad trend and not the real picture. TRUE FALSE 26 / 26 Q.1 The amounts spent on 5 components of a product are 30%, 20%, 20%, 15% and 15% respectively, by what per cent will the cost of the product increase ? 11.25% 11.03% 11.25% 12.15% Your score is LinkedIn Facebook Twitter VKontakte
