Business Analytics Report: Stock Performance Analysis Using Descriptive Statistics and Graphical Representation
Overview
This assessment requires students to apply business analytics techniques to analyze 10 years of stock performance data from a publicly traded company. The report demonstrates the transformation of raw data into meaningful business information through graphical representation (scatterplots and histograms) and descriptive statistics (mean, median, mode, standard deviation), with explicit connections to business implications and evidence-based recommendations.
What this coursework covers
- Introduction to business analytics and inferential statistics principles
- Methodology for data collection and analysis of 10-year stock performance
- Graphical representations and descriptive statistical analysis
- Business interpretation and implications of analytical findings
- Evidence-based recommendations and conclusions
Preview
MBA-FPX5008 Assessment
Assessment 2
Using Analytic Techniques to Add Meaning to Data and Applying Analytic Techniques to Business
InstructionsResourcesActivity 1Activity 2Attempt 1availableAttempt 2Attempt 3
InstructionsResourcesActivity 1Activity 2Attempt 1 availableAttempt 2Attempt 3
Write an 8-10 page professional business analytics report analyzing 10 years of stock performance data for a publicly traded company operating in a single industry.
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Introduction
Business analytics techniques facilitate decision making by transforming large amounts of raw data into meaningful information. Many businesses rely on analysis of relevant historical data to make key strategic and operational decisions. In business analytics, you often need to draw conclusions about a population of interest, but gathering data on the entire population may not be feasible. In these cases, data are gathered from a sample or subset of the population, and analyses done on the sample are used to draw inferences regarding the overall population—a process referred to as inferential statistics. The smaller group (the sample) provides measurements (the statistic) that serve as estimates for the larger group (the population) and its true measurement (the parameter). Rather than restricting estimates to single numbers that would be exactly correct or incorrect, analysts calculate confidence intervals—ranges of possible values within which there can be a certain percent confidence that the true population parameter falls.
Creating meaningful information from raw data involves two essential steps: first, representing data effectively in graphical format and calculating required statistics; second, interpreting those graphics and statistics to apply them in the business context.