Identify data and statistical techniques to solve real-world

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Reference no: EM134023142

Statistics and Applied Analytics

Assessment Task - Statistical Competency

Learning Outcome
a) Identify data and statistical techniques to solve real-world problems.

Assessment Task

This assessment requires you to perform the following tasks:

Qualify variables in a dataset using descriptive statistics.
Identify any data issues with the variables based on the statistical analysis.
Use appropriate techniques to correct the problems identified during the analysis. Please refer to the Instructions (below) for details on how to complete this task.

Context

Organisations keep records of events, transactions and other activities that capture reality. These records produce data that can be used to better understand everyday practices (e.g., what happened in reality) and support decisions. However, it is difficult for organisations to retrospectively document everyday practices, which are complex and fluid. This record-keeping challenge directly affects analytical processes within organisations, and absent or poor-quality data can lead to poor decisions. Understanding the data as a representation of reality is essential to performing a good and valuable analysis that supports better decisions.

The quality of data can be evaluated using descriptive statistics. Modern tools can automate and enhance this statistical process. However, these tools cannot replace practical experience, making business understanding and the ability to translate mathematics into reality highly valuable skills. Concepts related to data mining are also valuable when preparing data for reliable analytical outcomes.

Instructions

In this assessment, you will evaluate the data quality of a dataset using statistical methods. The goal is to ensure that the data represent reality well, are useful for analysis, and ultimately facilitate decision making.

Note: Your learning facilitator will provide details about the dataset assigned to you. To complete this assessment, you must complete the following high-level tasks:

Access SAS Viya statistical software to perform the analysis.
Obtain the dataset, and load it in the analytical environment.
For each of the variables in the dataset:

identify the data type
compute relevant descriptive statistics
create charts with relevant visualisation for the data distribution
interpret the results
identify and explain any data issues
determine and explain an approach to correct any existing problems
apply corrective measures to fix any existing data issues.

Write a 900-word document outlining the cleansing process performed and findings, including statistics, charts, data quality problems (if any) and corrections (if any). Ensure that you:

describe the dataset, including the source and overall characteristics
describe the tools and processes used
provide detailed information for each variable
check that spelling, grammar and punctuation are correct
use a consistent style for the presentation, including titles, paragraphs and visual elements
check that charts are correct, legible, without distractions and have good resolution.

When discussing the statistical results and interpretation, applying statistical hypothesis testing principles can help support valid analytical conclusions.

Include an appendix with a screenshot of your computer showing:

the date and time
your image captured from the computer's camera
the application software with your identification
relevant code, results and logs.

Note: Read the assessment rubric, which is an evaluation guide with criteria for grading your assessment. This will indicate what features a successful document should exhibit.

Referencing

It is essential that you use current APA style for citing and referencing the sources.

Reference no: EM134023142

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