TAILIEUCHUNG - Ebook Better business decisions from data - Statistical analysis for professional success: Part 2

(BQ) Part 2 book "Better business decisions from data - Statistical analysis for professional success" has contents: Relationships with numerical data, relationships with descriptive data, multivariate data, forecasting from known distributions, control charts,.and other contents. | P A RT V Relationships It is the function of creative men to perceive the relations between thoughts, or things, or forms of expression that may seem utterly different, and to be able to combine them into some new forms—the power to connect the seemingly unconnected. —William Plomer We now progress from considering a single variable to considering whether two quite different variables are related in some way. In the proper terminology, we are moving from univariate data to bivariate data and searching for relationships between two variables. We shall also consider relationships between more than two variables. CHAPTER 13 Cause and Effect Storks and Birth Rates We human beings seem to have an inbuilt desire to seek out relationships between different observed effects, and deduce a cause-and-effect ­ ssociation. a I suppose that survival depends to some extent on recognizing ­ elationships r and assuming that one effect causes another. As youngsters we learn of danger by relating climbing to the risk of falling. Crossing the road without looking is related to the possibility of being struck by a vehicle, and so on. However, we are inclined to imagine relationships where none exist, and, worse still, to imagine that these relationships imply cause and effect. The extreme situation is in the area of superstition: a remarkably high percentage of the population avoid the number thirteen or carry lucky charms. Astrology, which claims that events in our lives are affected by the positions of the planets, has a large following. Of course, relationships can be a first step in indicating the presence of cause and effect. Science and technology have advanced, and still advance, by studying relationships. Meteorologists establish relationships between the features of air movements and the resulting weather. Chemists establish relationships between the constituents of substances and their properties. In scientific investigations carried out under .

• Ngân hàng - Tín dụng
• Known distributions
• Control charts
• Multivariate data
• Relationships with descriptive data
• Better business decisions
• Time series
• Econometric time series
• Applied econometric time series
• Lecture Applied econometric time series
• Chuỗi thời gian
• Kinh tế lượng
• Stationary time series models
• Intervention analysis
• Multiequation time series models
• Time Series Forecasting
• Components of Time Series
• Evaluation Methods of Forecast
• Smoothing Methods of Time Series
• Time series models
• Components of a time series
• Trend component
• An Overview on Time Series Data Mining
• Similarity Search in Time Series Data
• Feature based Dimensionality Reduction
• Other Time Series Data Mining Tasks
• Data Mining
• Cobweb model
• Modeling volatility
• Error correction models
• Nonlinear models
• Doctoral Dissertation
• Application of Markov chain models
• Markov chain models and fuzzy time series
• Time series modeling
• Fuzzy rules of time series
• Higher Markov chains
• Doctoral thesis summary
• Similarity search
• Time series stream
• Dynamic time warping
• Data normalization
• Multiple time series streams
• Time series prediction
• Combination of long short term memory
• Structural time series models
• Structural models
• Hybrid model
• Journal of Science and Technology
• The partitioning method
• Hedge algebras for fuzzy time series forecasting
• Fuzzy time series forecasting
• The accuracy of forecasting
• Forecasting time series
• Hedge algebras
• Particle swarm optimization
• Fuzzy time series
• Stochastic trends
• Models with trend
• Frequent temporal inter object pattern
• Temporal pattern tree
• Temporal pattern mining
• Support count
• Time series mining
• Time series rule mining
• Permanent water bodies mapping
• Seasonal time series C band SAR data
• Water bodies mappin
• Time series analysis
• Synthetic Aperture Radar
• Undergraduate econometrics
• Lecture Undergraduate econometrics
• Time series data
• Stationary time series
• Spurious regressions
• Nitrogen content
• Forecasting of nitrogen content
• Soil by hybrid time series model
• Hybrid time series model
• Stochastic time series model
• Autoregressive models
• Akaike information criterion
• Box Pierce portmanteau
• Autoregressive time series model
• Enrollment forecasting based
• Linguistic time series
• Forecasting model
• Linguistic logical relationship
• Machine learning techniques
• Quantitative share price prediction
• S uitability of ARIMA model
• Goodness of fit
• Modelling and structural time series model
• Structural time series model
• Chickpea production
• Forecasting of chickpea production