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Assessment Task Information (In-College & Remote delivery)

Key details:

Assessment title:

Statistical Investigation

Module Name:

Advanced Statistics

Module Code:

PM608

Tutor’s Name:

tbc

Assessment will be set on:

Cycle 3 Week 3

Feedback opportunities:

Weekly progress check with Tutor.

Assessment is due on:

Cycle 3 Week 5

Assessment weighting:

50%

Assessment Instructions

What do you need to do for this assessment?

Task:

You will have to produce a statistical report from a collection of given datasets. You will receive a data set and scenario(s). Using your analysis of the data you will have to make a written recommendation.

You will have to work in Excel for many of the tasks, but you will then need to transfer data into a Microsoft Word document for your final report.

You will have approximately 3 weeks to complete the report and you will have to update your tutor with your progress on a weekly basis.

Guidance:

For this assessment you should make use of the following formative activities that you have already completed.  These activities have been designed to support this summative assessment:

· Cycle 3: The Use of MS Excel for Statistical Data Analysis

Please note:

This is an individual assessment so you should not work with any other student.

Before you submit this assessment, you will have an opportunity to update your tutor on your progress and receive advice.

Structure:

Example:

Your investigation should be presented in two main sections:

1: You should include a full numerical summary of the data in the study. You should include an explanation of the factors, types and any lurking variables which may be present in the study and any future research. You should highlight any possible errors in measurement, data anomalies or outliers and describe their effect on your conclusions. You should describe any correlation between the variables, if present.

Whatever your recommendations are – they must be clearly supported by your calculations using the supplied study data

2: Your task is to analyse the study data and present your recommendations

You should summarize any findings in the form of supported recommendations. The clarity of these recommendations and their reasons are paramount. Therefore, you should not use any statistical ‘jargon’ in your recommendations or in your justification for your recommendations.

Theory and/or task resources required for the assessment:

1: You will have to demonstrate skills in finding the measures of location and spread and creating charts. You will also need to compare scores on different datasets.

2: You will have to demonstrate skills in creating scatter graphs, finding correlation and regression coefficients, and interpreting these results.

3: You will have to demonstrate skills in random sampling, constructing grouped frequency tables, graphing data sets, and calculating confidence intervals.

4: You will have to demonstrate skills in the use of Microsoft Excel for data analysis.

5: You will have to make a reasoned written recommendation based on your analysis of the data.

Referencing style:

Not applicable

Expected word count:

Approximately 600 words. This does not include figures, diagrams, tables, and calculations.

Learning Outcomes Assessed:

· Critique original research data sets relevant to their field of study selecting appropriate statistical methods

· Discuss the relevance, validity and reliability of statistical methods in the context of experimental design

· Evaluate and interpret scientific information and data, both qualitative and quantitative, relevant to applications of their subject area

Submission Requirements:

You must include the following paragraph on your title page:

I confirm that this assignment is my own work.

Where I have referred to academic sources, I have provided in-text citations and included the sources in the final reference list.

When you submit a copy of your Report to Turnitin, you must include a title page with the following information:

· Module Code (PM608)

· Class/Group (e.g. Group A)

· Module Title (Advanced Statistics)

· Assessment Type (Statistical Analysis)

· Module Tutor Name

· Student ID Number

· Date of Submission

You must type your assessment in an academically suitable font (e.g. Arial), font size 12, with single spacing.

You must submit the assessment electronically via the VLE module page.  Please ensure you submit it via Turnitin.

Assessments submitted after the submission deadline may incur penalties or may not be accepted.

Additional submission information – check you have done the following:

Formatting

Consistent font, spacing, page numbers, formatting and subheadings

Citations

Correct format and location throughout the report

Referencing

Harvard referencing system used correctly in the reference list

Summarising

Summarising the results of research (if applicable)

Paraphrasing

Paraphrasing the contents of research findings (if applicable)

Spell check

Spell check the report

Proof-reading

Proof-reading completed

Grammar

Grammarly has been used to check the report

How will this assessment be marked?

Example: The assessment will be marked using the following areas and weightings:

· Analysis and presentation of graphical and numerical summaries (40%)

· Around 200-400 words for technical analysis and 100-300 words for business English conclusion / recommendations

· Interpretation of analysis (30%)

· Include conclusions reached.

· Demonstration of engagement with data and critique of pilot study (10%)

· Engagement with data is clearly demonstrated, and a summary is written using terminology presented entirely within the case study.

· The report is not presented as a list of statistical methods.

· Detailed and rational critique of data, experimental design and research (10%)

· Conclusion and recommendations (10%)

You will receive a % mark in each of these categories.  The overall mark will be a percentage (0-100%).

How will you get feedback?

Your tutor will mark the assessment and provide you with feedback.  You should use this feedback to guide your further learning on the module.