Making Numerical Predictions For Time Series Data - Part 1/3

Welcome to the Course 2 lectures 07:51 Introduction to the Course preview Course Contents preview Welcome to the Course 2 lectures 07:51 Introduction to the Course preview Course Contents preview Introduction to the Course preview Introduction to the Course preview Introduction to the Course preview Introduction to the Course preview Course Contents preview Course Contents preview Course Contents preview Course Contents preview Introduction to Time Series Data 1 lecture 08:12 A look at Time Series Data preview Generally, it is seen that forecasting involves studying the behaviour of a characteristic over time and examining data for a pattern. The forecasts are made by assuming that, in future, the characteristic will continue to behave according to the same pattern.A Time Series is a collection of observations made sequentially over a period of time. Introduction to Time Series Data 1 lecture 08:12 A look at Time Series Data preview Generally, it is seen that forecasting involves studying the behaviour of a characteristic over time and examining data for a pattern. The forecasts are made by assuming that, in future, the characteristic will continue to behave according to the same pattern.A Time Series is a collection of observations made sequentially over a period of time. A look at Time Series Data preview Generally, it is seen that forecasting involves studying the behaviour of a characteristic over time and examining data for a pattern. The forecasts are made by assuming that, in future, the characteristic will continue to behave according to the same pattern.A Time Series is a collection of observations made sequentially over a period of time. A look at Time Series Data preview Generally, it is seen that forecasting involves studying the behaviour of a characteristic over time and examining data for a pattern. The forecasts are made by assuming that, in future, the characteristic will continue to behave according to the same pattern.A Time Series is a collection of observations made sequentially over a period of time. A look at Time Series Data preview Generally, it is seen that forecasting involves studying the behaviour of a characteristic over time and examining data for a pattern. The forecasts are made by assuming that, in future, the characteristic will continue to behave according to the same pattern.A Time Series is a collection of observations made sequentially over a period of time. A look at Time Series Data preview Generally, it is seen that forecasting involves studying the behaviour of a characteristic over time and examining data for a pattern. The forecasts are made by assuming that, in future, the characteristic will continue to behave according to the same pattern.A Time Series is a collection of observations made sequentially over a period of time. Generally, it is seen that forecasting involves studying the behaviour of a characteristic over time and examining data for a pattern. The forecasts are made by assuming that, in future, the characteristic will continue to behave according to the same pattern.A Time Series is a collection of observations made sequentially over a period of time. Generally, it is seen that forecasting involves studying the behaviour of a characteristic over time and examining data for a pattern. The forecasts are made by assuming that, in future, the characteristic will continue to behave according to the same pattern.A Time Series is a collection of observations made sequentially over a period of time. Moving Averages 6 lectures 01:05:17 Using Descriptive Statistics to Predict Values Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread).A simple, but widely used, strategy to predict future demand is to use central tendencies of past data to be used as the future demand. Predicting using Moving Averages Moving Averages Prediction is another simple, but powerful, way to predict future values based on historic data. Moving Averages takes in to consideration recency of data. Centred Moving Averages preview A more popular variation of Moving Averages is Centred Moving Averages. This video discussed using Centred Moving Averages for Predicting Future Value. Weighted Moving Averages Weighted Moving Averages is a more powerful tool for predicting future values as it has mechanism to give more priority to factors like RECENCY of data. Calculating Standard Deviation for Prediction made using Moving Averages One of the methods for finding confidence in the predictions made using Moving Averages is by determining and interpreting the Standard Deviation of the Predictions. Predicting for Seasonal Data In this video, we discuss technique for predicting future values when the Time Series Data has Seasonality Component. Moving Averages. 6 lectures 01:05:17 Using Descriptive Statistics to Predict Values Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread).A simple, but widely used, strategy to predict future demand is to use central tendencies of past data to be used as the future demand. Predicting using Moving Averages Moving Averages Prediction is another simple, but powerful, way to predict future values based on historic data. Moving Averages takes in to consideration recency of data. Centred Moving Averages preview A more popular variation of Moving Averages is Centred Moving Averages. This video discussed using Centred Moving Averages for Predicting Future Value. Weighted Moving Averages Weighted Moving Averages is a more powerful tool for predicting future values as it has mechanism to give more priority to factors like RECENCY of data. Calculating Standard Deviation for Prediction made using Moving Averages One of the methods for finding confidence in the predictions made using Moving Averages is by determining and interpreting the Standard Deviation of the Predictions. Predicting for Seasonal Data In this video, we discuss technique for predicting future values when the Time Series Data has Seasonality Component. Using Descriptive Statistics to Predict Values Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread).A simple, but widely used, strategy to predict future demand is to use central tendencies of past data to be used as the future demand. Using Descriptive Statistics to Predict Values Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread).A simple, but widely used, strategy to predict future demand is to use central tendencies of past data to be used as the future demand. Using Descriptive Statistics to Predict Values Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread).A simple, but widely used, strategy to predict future demand is to use central tendencies of past data to be used as the future demand. Using Descriptive Statistics to Predict Values Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread).A simple, but widely used, strategy to predict future demand is to use central tendencies of past data to be used as the future demand.Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread).A simple, but widely used, strategy to predict future demand is to use central tendencies of past data to be used as the future demand.Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread).A simple, but widely used, strategy to predict future demand is to use central tendencies of past data to be used as the future demand. Predicting using Moving Averages Moving Averages Prediction is another simple, but powerful, way to predict future values based on historic data. Moving Averages takes in to consideration recency of data. Predicting using Moving Averages Moving Averages Prediction is another simple, but powerful, way to predict future values based on historic data. Moving Averages takes in to consideration recency of data. Predicting using Moving Averages Moving Averages Prediction is another simple, but powerful, way to predict future values based on historic data. Moving Averages takes in to consideration recency of data. Predicting using Moving Averages Moving Averages Prediction is another simple, but powerful, way to predict future values based on historic data. Moving Averages takes in to consideration recency of data.Moving Averages Prediction is another simple, but powerful, way to predict future values based on historic data. Moving Averages takes in to consideration recency of data.Moving Averages Prediction is another simple, but powerful, way to predict future values based on historic data. Moving Averages takes in to consideration recency of data. Centred Moving Averages preview A more popular variation of Moving Averages is Centred Moving Averages. This video discussed using Centred Moving Averages for Predicting Future Value. Centred Moving Averages preview A more popular variation of Moving Averages is Centred Moving Averages. This video discussed using Centred Moving Averages for Predicting Future Value. Centred Moving Averages preview A more popular variation of Moving Averages is Centred Moving Averages. This video discussed using Centred Moving Averages for Predicting Future Value. Centred Moving Averages preview A more popular variation of Moving Averages is Centred Moving Averages. This video discussed using Centred Moving Averages for Predicting Future Value. A more popular variation of Moving Averages is Centred Moving Averages. This video discussed using Centred Moving Averages for Predicting Future Value. A more popular variation of Moving Averages is Centred Moving Averages. This video discussed using Centred Moving Averages for Predicting Future Value. Weighted Moving Averages Weighted Moving Averages is a more powerful tool for predicting future values as it has mechanism to give more priority to factors like RECENCY of data. Weighted Moving Averages Weighted Moving Averages is a more powerful tool for predicting future values as it has mechanism to give more priority to factors like RECENCY of data. Weighted Moving Averages Weighted Moving Averages is a more powerful tool for predicting future values as it has mechanism to give more priority to factors like RECENCY of data. Weighted Moving Averages Weighted Moving Averages is a more powerful tool for predicting future values as it has mechanism to give more priority to factors like RECENCY of data.Weighted Moving Averages is a more powerful tool for predicting future values as it has mechanism to give more priority to factors like RECENCY of data.Weighted Moving Averages is a more powerful tool for predicting future values as it has mechanism to give more priority to factors like RECENCY of data. Calculating Standard Deviation for Prediction made using Moving Averages One of the methods for finding confidence in the predictions made using Moving Averages is by determining and interpreting the Standard Deviation of the Predictions Linear Regression Linear regression is used to predict the value of a continuous variable Y based on one or more input predictor variables X. The aim is to establish a mathematical formula between the the response variable (Y) and the predictor variables...