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Which of the following model does not fall in time series models?
- a)Moving average
- b)Linear regression
- c)Exponential smoothing
- d)Trend projection
Correct answer is option 'B'. Can you explain this answer?
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Which of the following model does not fall in time series models?a)Mov...
Time Series Models: Uses a series of data points to predict future demand.
Associative Model: Uses variables and factors that affect the future demand.
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Which of the following model does not fall in time series models?a)Mov...
Explanation:
Moving Average:
Moving average is a time series model that is used to smooth out the fluctuations in data by calculating the average of a fixed number of data points over a specified time period. It is a commonly used model in time series analysis.
Linear Regression:
Linear regression is a statistical model that is used to establish a relationship between a dependent variable and one or more independent variables. It is typically used to predict future values based on historical data.
Exponential Smoothing:
Exponential smoothing is a time series model that is used to forecast future values based on the weighted average of past observations, with more recent observations being given more weight. It is commonly used for short-term forecasting.
Trend Projection:
Trend projection is a time series model that is used to forecast future values based on the assumption that the underlying trend in the data will continue. It involves fitting a trend line to the historical data and extending it into the future to make predictions.
Conclusion:
Out of the given options, linear regression is the only model that does not fall under time series models. Linear regression is a model used to establish a relationship between variables, but it does not explicitly consider the temporal order of the data. In time series analysis, the focus is on analyzing and forecasting data that is collected over time, taking into account the patterns and trends within the data. Therefore, linear regression is not a time series model.
Moving Average:
Moving average is a time series model that is used to smooth out the fluctuations in data by calculating the average of a fixed number of data points over a specified time period. It is a commonly used model in time series analysis.
Linear Regression:
Linear regression is a statistical model that is used to establish a relationship between a dependent variable and one or more independent variables. It is typically used to predict future values based on historical data.
Exponential Smoothing:
Exponential smoothing is a time series model that is used to forecast future values based on the weighted average of past observations, with more recent observations being given more weight. It is commonly used for short-term forecasting.
Trend Projection:
Trend projection is a time series model that is used to forecast future values based on the assumption that the underlying trend in the data will continue. It involves fitting a trend line to the historical data and extending it into the future to make predictions.
Conclusion:
Out of the given options, linear regression is the only model that does not fall under time series models. Linear regression is a model used to establish a relationship between variables, but it does not explicitly consider the temporal order of the data. In time series analysis, the focus is on analyzing and forecasting data that is collected over time, taking into account the patterns and trends within the data. Therefore, linear regression is not a time series model.
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Which of the following model does not fall in time series models?a)Moving averageb)Linear regressionc)Exponential smoothingd)Trend projectionCorrect answer is option 'B'. Can you explain this answer?
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