Module Title: Applied Statistics for Data Science
Module Code: MS4S08

ASSESSMENT DESCRIPTION

Task A

In a study commissioned by a UK weather agency, a research institution was tasked
with analysing historical weather data to understand factors influencing weather
patterns across different regions in the UK. The dataset includes key weather variables
and several demographic and geographic factors such as Region, Month,
Temperature, Rainfall, and Sun Hours.
The primary objective of the analysis is to examine relationships between these
variables and to identify any rogue values (outliers) that might distort the findings.
Additionally, the agency hypothesizes that the variable Rainfall can be modelled
linearly using Temperature, Sun Hours, and Region. The research institution seeks
to validate this hypothesis.
The structure for reporting each part of this task should be:

  • Summarise the key results obtained from the analysis, marks are awarded for
    both the suitability and correctness of the approach (10%)
  • Make overall conclusions from the data based on the output obtained 5%)
  • Produce a range of visualisation summarising the key findings (5%)

Task B

In a study aimed at understanding customer behaviour, researchers seek to analyse
a dataset capturing customer demographics and survey responses (Customer
Personality Analysis). The focus is on uncovering the underlying constructs that
summarize customer preferences and behaviours and identifying the most influential
factors among the surveyed variables. Additionally, they aim to compare these latent
constructs across demographic groups to observe potential variations.
To achieve this, dimensionality reduction will be employed to simplify the dataset while
retaining key information. Researchers are particularly interested in understanding the
interrelationships between variables and have suggested factor analysis as a possible
method but are uncertain about its suitability.
You are required to carry out this analysis on behalf of the research institute. The structure
for reporting on this task should be:

  • Outline the purpose of the analysis (5%)
  • Describe the methods used to look at the data (5%)
  • Summarise the key results obtained from the analysis, marks are awarded for
    both the suitability and correctness of the approach (15%)
  • Make overall conclusions from the data based on the output obtained (5%)

Task C

A company seeks to gain insights into employee motivations and satisfaction by identifying
distinct groups of employees who exhibit similar satisfaction patterns. To achieve this, a
survey was conducted where employees rated their satisfaction levels (on a scale of 0–100,
with 100 being the highest) across several factors: Job Satisfaction, Pay Satisfaction, WorkLife Balance, and Team Dynamics. The data is provided in the Employee Satisfaction
Survey dataset.
The company has requested an analysis that includes two key components. First, a Cluster
Analysis will be conducted to group employees based on their satisfaction scores, enabling
a better understanding of motivational patterns across the workforce. Second, a Cluster
Feature Analysis will evaluate the key characteristics of the identified clusters. This involves
performing statistical tests to determine whether there are significant differences in the
original satisfaction variables (e.g., Job Satisfaction, Pay Satisfaction) across the clusters,
providing actionable insights into employee satisfaction and motivation.
A suggested structure for the reporting for this task would be:

  • Outline the purpose of the analysis (5%)
  • Describe the methods used to look at the data (5%)
  • Summarise the key results obtained from the analysis, and complete further
    statistical testing as required, marks are awarded for both the suitability and
    correctness of the approach (15%)
  • Make overall conclusions from the data based on the output obtained (5%)

LEARNING OUTCOMES ASSESSED

LO1

Learning Outcome 1:To understand the concepts and theory of statistical analysis, and explain the
wider context of their value in Data Science.  
LO2

Learning Outcome 2: Determine and use statistical techniques to assess practical situations and
interpret real-world complex data.

GET THIS ASSIGNMENT READY FOR £199 WITH NO HIDDEN OR EXTRA CHARGES. 100% ORIGINAL WORK IS GUARANTEED ALONG WITH THE TURNITIN FILE.

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