Task-1 Data Analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data. Indeed, researchers generally analyze for patterns in observations through the entire data collection phase. Data analysis is primarily used for prediction and identification, as well as the use of evidentiary principles such as falsifiability, validity, and parsimony to guide the analysis. As a result, there is a strong correlation between excellent decision-making and success. Many businesses desire to employ data analysis to better understand patterns, forecast outcomes, and enhance their business choices. It's critical to understand when and how to use the data analysis approach on certain types of data. With an example .

diagram, applications, and advantages and disadvantages, describe the following data analysis methodologies.

a) Discriminate Analysis (DA)

b) Cluster Analysis (CA)

c) Regression Analysis (RA)

d) Structural Equation Modeling (SEM)

Note: (For each critical analysis with 150 informatic words and at least two in-text sources required.)