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Management School – Undergraduate Coursework Specification

Module Code: MGT223

Coursework Code: MGT223-1

Module Title: Business Statistics

Date Available: March 18, 2024

Submission details: April 19, 2024, 12pm (noon).

Electronic submission only through Blackboard.

You can submit your assignment multiple times to the submission link on the module Blackboard site. Each time you submit you will receive a Similarity Report. You can check this and improve your referencing before the final deadline.

After 3 submissions you will need to wait 24hrs before you receive a new report.

Please note: each new submission replaces any previous submission. It is not possible to retrieve a previous submission.

Your final submission must be made before the deadline to avoid late penalties.

You should note that the time of submission is taken from once the document has been successfully uploaded and confirmed – this may take more than five minutes during busy periods. Late penalties will be applied to any work submitted from 12.01 pm on April 19 onwards. Details of calculating a late penalty can be found in your program Handbook. It is your responsibility to ensure the correct document/file has been uploaded successfully.

When submitting students must:

1. Include a completed cover sheet (available from Blackboard (MOLE))

2. Use ‘Student Number, MGTXXX-1’ (e.g. 200011001 mgt223-1) as the document’s file name and the Assignment Title in Turnitin.

You may find it helpful to submit the file in PDF format as this will preserve the formatting of statistical output etc.

Contribution to Final Mark for Module: 30%

Maximum Word Length: N/A

I have included suggested word counts but these are for guidance only and no penalty will be imposed if you go over/under them.

Requirements:

You are required to answer the question below.

The data is available in a separate Excel workbook.

ALL STATISTICAL ANALYSIS SHOULD BE UNDERTAKEN USING SPSS.

A manager is interested in understanding the impact of a new training program on improving the performance of her employees.

She has been provided with a data set comprising measures of the performance (using a standard performance assessment tool – the higher the score, the higher the performance) of two samples of 15 employees. One sample comprises employees who have not attended the new training (first column); the other sample comprises 15 employees who attended the training.

The data set that you have been assigned is available in the Excel workbook provided in the coursework folder.

a) Provide descriptive statistical and graphical summaries of the two sets of data.

(Suggested word count 200–300 words.)

b) Analyse the data using an independent samples t-test.

(Suggested word count 200–300 words.)

c) It now transpires that only 15 employees were involved in the trials, and their job performance was measured before and after the training program. Hence, each row of the data corresponds to an individual employee and its two performance measures (before and after training).

Analyse the data using a paired t-test.

(Suggested word count 100-200 words.)

d) Use a suitable non-parametric test to investigate the impact of the training program on employee performance

(Suggested word count 200-300 words.)

e) Compare the results of the tests conducted in parts (b), (c), and (d) and state, with an explanation, which test is most appropriate.

(Suggested word count 300-400 words.)

f) Provide a summary of your findings, suitable for inclusion in a management report.

(Suggested word count 100-200 words.)

The marking criteria focus on your technical ability and your ability to express the results clearly and concisely in technical and non-technical terms.

Your answer to parts (a), (b), (c), and (d) should include a full but concise interpretation of your analysis, stating and assessing where possible, any assumptions underpinning the tests and indicating any hypotheses that you are testing.

When answering parts (d), (e), and (f), you should assume that the information provided in part (c) about the structure of the data still applies.