Learning Outcomes By the end of this section, you should be able to: A machine learning (ML) model is a mathematical and computational model that attempts to find a relationship between input variables and output (response) variables of a dataset. The way…
Figure 6.1 Machine learning may be used to classify all kinds of data. Facial recognition technology relies heavily on machine learning algorithms, such as random forest models. (credit: modification of work “Humanoid Robot Uprising” by Steve Jurvetson/Flickr, CC BY 2.0) Chapter Outline…
Learning Outcomes By the end of this section, you should be able to: A time series forecast essentially predicts the middle of the road values for future terms of the series. For the purposes of prediction, the model considers only the trend…
Learning Outcomes By the end of this section, you should be able to: This section focuses on analysis of a time series into its components for the purpose of building a robust model for forecasting. Although much of the analysis…
Learning Outcomes By the end of this section, you should be able to: Time series data may be decomposed, or broken up into several key components. There may be an overall direction (up or down) that the data seems to be…
Learning Outcomes By the end of this section, you should be able to: Data can change over time, and it is important to be able to identify the ways that the data may change in order to make reasonable forecasts…
Figure 5.1 Time series analysis involves the examination of data points collected at specific time intervals; it is crucial for identifying trends and patterns that inform predictions and strategic decisions. (credit: modification of work “Bitcoin steigend” by Tim Reckmann/Flickr, CC BY 2.0)…
Learning Outcomes By the end of this section, you should be able to: In Testing Claims Based on One Sample, we reviewed methods to conduct hypothesis testing for two means; however, there are scenarios where a researcher might want to compare…
Learning Outcomes By the end of this section, you should be able to: We briefly introduced correlation analysis at the beginning of this chapter, but now we want to dig in a little deeper. Data scientists are often interested in knowing if…
Learning Outcomes By the end of this section, you should be able to: Constructing confidence intervals is one method used to estimate population parameters. Another important statistical method to test claims regarding population parameters is called hypothesis testing. Hypothesis testing is…