<<12345678910111213141516171819202122232425262728293031323334353637>> 1. What is Time Series in statistics?A technique for measuring spatial dataA statistical method for analyzing cross-sectional dataA statistical technique applied to measure time-based data over a time periodA method for calculating mean and medianQuestion 1 of 37 2. What is an example of time series data?The population of a cityThe length of a riverThe rate of inflation in the last 15 yearsThe average temperature of a cityQuestion 2 of 37 3. Y-f(t), what does 'Y' represent?The value of the variable at time 't'The function of time 't'The sum of values over timeThe product of values over timeQuestion 3 of 37 4. What are the possible values for 't' in time series analysis?Only hourly and dailyWeekly, monthly, and yearlyQuarterly and half-yearlyAll of the aboveQuestion 4 of 37 5. In the given time series plot description, what is represented by the variable 'X'?Gold prices (Rs.)TimeThe dependent variableThe function of timeQuestion 5 of 37 6. On the time series plot, which axis represents time?Y-AxisX-AxisZ-AxisNeither X nor Y-AxisQuestion 6 of 37 7. What is represented on the Y-Axis of the time series plot?Gold prices (Rs.)TimeThe dependent variableThe function of timeQuestion 7 of 37 8. What does the shape of the time series plot suggest about the trend in gold prices?Increasing trendDecreasing trendConstant trendThe information is not sufficient to determine the trendQuestion 8 of 37 9. What does the secular trend refer to in a time series?Short-term fluctuationsGeneral tendency over a long time periodRandom variationsSeasonal patternsQuestion 9 of 37 10. How can the secular trend behave in terms of the general tendency of the time series data?It always increasesIt always decreasesIt can increase, decrease, or remain constantIt is constant throughoutQuestion 10 of 37 11. What is a characteristic of a linear trend in a time series?The rate of change is not constantThe trend is always upwardsThe trend is always downwardsThe rate of change remains constantQuestion 11 of 37 12. In the given information, what is mentioned about the nature of the upward trend in the secular trend?It is always linearIt is always non-linearIt can be linear or non-linearThe information is not providedQuestion 12 of 37 13. What is trend analysis in statistics?Analyzing random fluctuations in dataStudying the long-term patterns or tendencies in dataIdentifying outliers in a datasetCalculating the mean of a datasetQuestion 13 of 37 14. When the trend in data can be described by a straight line, what is it called?Non-linear trendSeasonal trendLinear trendIrregular trendQuestion 14 of 37 15. What does the symbol Y represent in the context of trend analysis?The actual value of the dependent variableThe mean of the datasetThe estimated value of the dependent variableThe independent variableQuestion 15 of 37 16. In the equation for estimating a straight line in trend analysis, what does 'x' represent?The actual value of the dependent variableThe mean of the datasetThe estimated value of the dependent variableThe independent variableQuestion 16 of 37 17. What is the purpose of trend analysis in statistics?To identify random fluctuations in dataTo study the short-term patterns in dataTo analyze the long-term patterns or tendencies in dataTo calculate the median of a datasetQuestion 17 of 37 18. What is seasonal variation in a time series?Unpredictable and irregular movementsRepetitive and predictable movements around the trend line within a year or lessRandom fluctuations in dataLong-term patterns or tendenciesQuestion 18 of 37 19. To measure seasonal variations effectively, what time intervals should be considered?Years and decadesMonths and yearsDays and weeksCenturies and millenniaQuestion 19 of 37 20. What is the purpose of establishing the pattern of past changes in seasonal variation?To introduce randomness into the time seriesTo analyze long-term trendsTo calculate cyclical variationsTo predict future changesQuestion 20 of 37 21. What term is used to describe the process of eliminating seasonal variation from a time series?DeseasonalisationDetrendingSeasonal predictionTrend analysisQuestion 21 of 37 22. Once seasonal patterns are established, what does their elimination from the time series help calculate?Random fluctuationsLong-term trendsCyclical variationsFuture predictionsQuestion 22 of 37 23. According to classical time series analysis, what is the assumed relationship between the components of a time series?AdditiveMultiplicativeExponentialLogarithmicQuestion 23 of 37 24. What does the symbol 'O' represent in the multiplicative relationship equation O = T x S x C x I?Seasonal componentCyclical componentOriginal dataIrregular componentQuestion 24 of 37 25. In the multiplicative relationship equation, what does 'T' represent?TrendIrregular componentSeasonal componentCyclical componentQuestion 25 of 37 26. Which component of the time series represents repetitive and predictable movements around the trend line within a year or less?TrendSeasonal componentCyclical componentIrregular componentQuestion 26 of 37 27. How is the relationship between the components of the time series assumed to be in classical time series analysis?ExponentialLogarithmicMultiplicativeAdditiveQuestion 27 of 37 28. What are the methods for measuring the trend component in a time series?Graphic, Arithmetic, Moving AveragesSemi Averages, Curve Fitting, Least SquaresGraphic, Semi Averages, Moving Averages, Least SquaresExponential Smoothing, Seasonal Decomposition, Linear RegressionQuestion 28 of 37 29. Which method involves plotting the data points on a graph to visually analyze the trend?Semi AveragesGraphicMoving AveragesLeast SquaresQuestion 29 of 37 30. What does the method of Semi Averages involve in the measurement of trend?Taking the average of every two data pointsTaking the average of a group of data pointsPlotting data points on a graphFitting a curve using the principle of least squaresQuestion 30 of 37 31. Which method calculates the average of a fixed number of consecutive data points to smooth out fluctuations and identify the trend?GraphicSemi AveragesMoving AveragesLeast SquaresQuestion 31 of 37 32. What is the principle underlying the method of Least Squares in curve fitting for trend measurement?Minimizing the sum of squared differences between observed and estimated valuesMaximizing the sum of squared differences between observed and estimated valuesMinimizing the number of data pointsMaximizing the number of data pointsQuestion 32 of 37 33. What is the underlying assumption in time series forecasting when using historical trends?The future will always be the same as the pastThe future trends will be completely different from the pastThe future trends will hold similar to historical trendsHistorical trends have no impact on future eventsQuestion 33 of 37 34. In an Autoregressive Model (AR model), how is the variable of interest forecasted?By regressing the variable on its own lagged valuesBy considering the moving average of the variableBy analyzing the residuals of the variableBy predicting the variable based on external factorsQuestion 34 of 37 35. What does the Moving-average model (MA model) involve in terms of modeling univariate time series?Regressing the variable on its own lagged valuesModeling the error term as a linear combination of concurrent and past error termsAnalyzing the residuals of the variablePredicting the variable based on external factorsQuestion 35 of 37 36. What is the Autoregressive Moving Average model (ARMA model) a combination of?AR and MA modelsLinear and non-linear modelsSimple and complex modelsUnivariate and multivariate modelsQuestion 36 of 37 37. How does an ARMA model describe time series?In terms of one polynomial for moving averageIn terms of two polynomials for auto regression and moving averageIn terms of a single polynomial for auto regressionIn terms of a single polynomial for moving averageQuestion 37 of 37 Loading...