Reference no: EM134032205 , Length: Word Count:1500

Statistics and Applied Analytics

Assessment - Data Analysis

Learning Outcome 1: Collect and transform data for analysis.
Learning Outcome 2: Analyse data using appropriate statistical tools and techniques.

Assessment Task

This assessment requires you to perform the following tasks:

Use appropriate techniques to correct the data issues identified during the data quality phase.
Identify relevant approaches to solve problems working with available data. Please refer to the Instructions (below) for details on how to complete this task.

Context

Data are invaluable for understanding past and present reality, and facilitating decision making. To transform data into educated predictions that enable decision making, the quality and quantity of the data must be reliable. Additionally, appropriate statistical techniques such as inferential statistics must be applied. These techniques contain various approaches for identifying patterns and making predictions that can guide practical actions, assuming a stable environment.

Governments and organisations of various types and sizes can use these techniques to optimise key factors, such as profit, resource use and maximum output, and reduce losses and waste. Concepts related to correlation and causation and confidence intervals are commonly used when interpreting statistical results.

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.

You will create a question that inferential statistical techniques can answer. You will then apply inferential statistical methods to create a model capable of making predictions.

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 the SAS Viya statistical software to perform the analysis.
Obtain the dataset and load it in the analytical environment.
Perform the data analysis and correct any data issues.
Familiarise yourself with the data, and clean the dataset, and then create a question that inferential statistics can answer.
Create a relevant model using inferential statistical methods capable of answering the question.

Write a 1,500-word document that:

describes the dataset
describes the context that the data represent
states the question, and explains why it is relevant
proposes a technique, and explains why it is suitable to answer the question
shows the inferences or predictions generated by the model
presents relevant metrics about the model's performance and its interpretation in the context of the question
has been checked to ensure the spelling, grammar and punctuation are correct
uses a consistent style for the presentation, including titles, paragraphs and visual elements
includes correct, legible charts, without distractions and with a good resolution. Applying methods such as Analysis of Variance (ANOVA) may be appropriate where supported by the dataset and research question.

Include in an appendix 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.

Referencing

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