School of Management
MN-2517 Statistics 2 for Business
Module Overview
Introduction
This module extends the first year maths/statistics module taken to provide tools and techniques in statistics using SPSS and AMOS computer packages to perform the analysis.
This booklet contains:
an introduction to the module
lecture and seminar locations
details of recommended reading
information on assessment and feedback, including coursework-item briefs
an overview of the entire module
Lecture & Seminar Locations
Lectures/seminars will take place in SOM117 on Tuesday 12:00-15.00 School of Management.
Please note: lecture/seminar locations may change in the first two weeks of term.
Communication
Lecture notes will be posted on Blackboard along with any administrative notices.
Reading Material
Reading Material
A simple guide to IBM SPSS statistics for version 20.0 / Lee A. Kirkpatrick, Brooke C. Feeney. Wadsworth, Cengage Learning 2013.
Statistics for the terrified / John H. Kranzler (5th ed.) Pearson Prentice Hall 2011.
SPSS Survival manual: a step by step guide to data analysis using IBM SPSS / Julie Pallant (5th ed). McGraw Hill 2013.
A core textbook is only a starting point and provides introductory and background information only. To achieve high marks in this module students will need to do the background and supplemental reading as well as conduct their own independent research for instance through the reading of academic journals, into the topics identified.
Assessment and Feedback
The assessment for the module is structured as follows:
2 x 50% individual coursework assignment of 2000 words
Resit – Examination worth 100% of the overall Module Mark
Feedback on the coursework will normally be provided within three calendar weeks of submission. All feedback for the coursework assignment will be provided through GradeMark. Marks will be made available via Grade Centre in Blackboard and your university student portal. Please note that all marks are provisional until they have been ratified by a progression or award board and are therefore subject to change. Anonymous examples of good and bad practice will be shown in the final week of the module.
If you fail this module you will be required to sit an examination during the supplementary/resit assessment period. The resit coursework will be weighted as 100% of the overall module mark – the initial assessment weightings do not apply for resits.
Moderation of Marks
The University-wide policy on double marking is published in the Academic Guide:
www.swan.ac.uk/registry/academicguide/assessmentandprogress/doubleMarkingpolicy/
The School of Management normally employs the approach of second marking as sampling and for dissertations universal non-blind double marking.
School of Management
MN-2517 Statistics 2 for Business
Individual Coursework Assignments
1) Individual Coursework Assignment 1
This assignment is worth 50% of the overall module mark and consists of 2 parts (Part I and Part II).
Part I. Task Brief
For this coursework Part I you are required to perform an independent samples t-test using SPSS. Your solution should be word-processed and submitted electronically. Your solution should include any output produced from the analysis, and an account of the methods you used to obtain that output.
The problem:
Data file. Creditpromo
This is a hypothetical data file that concerns a department store’s efforts to evaluate the effectiveness of a recent credit card promotion (in dollars spent by cardholders). To this end, 200 cardholders were randomly selected. Half received an ad promoting a reduced interest rate on purchases made over the next three months. Half received a standard seasonal ad.
Your task is to perform analysis to find out if the type of an advertisement had an impact on the amount of dollars spent by credit holders.
Perform a suitable independent samples t-test on this data.
You should address the following questions, explaining your answers in detail:
What is the population from which this sample was drawn?
What is the purpose of Levene’s Test? – Explain why it is important that Levene’s Test is included in the output for this independent samples t-test
What is the Null hypothesis for Levene’s Test?
Do we accept or reject the null hypothesis for Levene’s Test? – Explain why.
Which of the two t-tests labelled “Equal variances assumed” and “Equal variances not assumed” should we use? – Explain why.
In order to apply the t-test, what assumption do we make about the distribution of the errors?
What is the null hypothesis for the t-test?
Do we accept or reject the null hypothesis for the t-test? – Explain why.
Is it appropriate to use a one-tailed or two-tailed test here? – Explain why.
What overall conclusion can we draw from this output? – include a reference to the minimum difference between the amount of dollars spent by credit holders who received a standard seasonal ad and those who received a promotional ad. that you would expect to find in the population.
Part II. Task Brief
For this coursework part II you are required to solve a regression problem using SPSS. Your solution should be word-processed and submitted electronically. Your solution should include any output produced from the analysis, and a detailed account of the methods you have used, the reasons you have chosen those particular methods, and the conclusions you have drawn.
The problem:
Data file. Car sales.
This data file contains hypothetical sales estimates and list prices for various makes and models of vehicles.
Analysts for a car sales company are aware that sales of cars depend on car prices, and would like to determine the relationship between list prices and sales more precisely. They collect data on list prices (in thousands of monetary units) and sales (thousands of cars) for six weeks.
Produce a suitable graph to investigate the relationship between the two variables, and report your findings.
Perform an appropriate regression analysis in SPSS, to predict sales figures given the price, and write a detailed report of your findings. Your report should address (but not necessarily be confined to) the following questions:
What percentage of the variation in car sales is accounted for by your model?
What is the equation of best fit, and how do you interpret the coefficients in your model?
By how much, on average, can we expect sales to increase if the list price increases by 10 points?
What assumptions are made about the distribution of the data. If you are able to test whether the assumptions appear to be true, report on your results.
On average, what level of sales can we expect when the list price is 10 thousand (of monetary units)?
In a “worst case scenario”, what is the lowest level of sales that we would expect when the price is 10 thousand (of monetary units)? (Use a confidence level of 95%.)
Key Marking criteria will include:
Accuracy of the calculations
Appropriateness of the methodology
Clarity and conciseness of the descriptions of the methodology
Word Limit
The word limit for this individual assignment is 2000 words.
The School of Management’s detailed word-limit policy, including the penalties relating to breaches of the specified word limit, are incorporated into the electronic cover sheet for coursework (available from the Assessment and Feedback folder on the Blackboard site for this module).
Submission
The full assignments must be submitted by 3pm on 13/03/2017 via Turnitin.
Please note:
The maximum file size that can be uploaded is 20mb. If your file is larger than this it is usually because you have included a lot of images – you should either remove some if possible, or else convert them to a more efficient format to bring the file size down (e.g. .png or .gif).
You should ensure your student number is in the title of the filename for the work you submit/upload.
The School of Management operates a late penalty system as follows: when work is submitted late with no prior authorisation, a penalty of 10% will be deducted from the actual mark for each calendar day, or part of a day, by which the deadline is exceeded. After seven days from the initial deadline, a mark of zero will be awarded. Late work should be submitted electronically in the usual way.
Digital Submission of Coursework Instructions
Logon to Blackboard.
Access the appropriate Module site.
Click the Assignment menu button which appears on the left of the screen.
In this folder you will see a file entitled ‘Student Declaration form’. You need to complete this form and incorporate it as the first page of your coursework (not two separate files).
Click Coursework. Please read the statement of originality before you click “submit”. By submitting work you are agreeing to this statement and confirming it to be true.
Complete the dialogue box with your forename and surname
To submit your coursework, locate the correct file on your computer by clicking the “browse” button and enter a title for the coursework (we suggest the module code and your student ID MNB108 123456). Click SUBMIT
You will then be asked to check if the document is the one you wish to submit and if so click “YES, SUBMIT”
You will then receive a message saying “paper successfully complete”.
BLACKBOARD will then send you a confirmation email of submission. Please keep this receipt safe as evidence of your submission.
If you experience any difficulties submitting your work via Turnitin please contact the Student Hub straight away.
Notes on Style & Word Count
The length limit for the assignment plan is one side of A4 paper. The text size should be 12 and the font Arial. The line spacing should be set to 1.2 as a minimum and the margins (all) should be a minimum of 1.9cm. References should be included on a separate page using the APA Harvard style of referencing.
This is a practical report, with an aim to present, analyse and describe your results, based on the task questions. The results should be interpreted with referencing to the relevant academic sources, such as textbooks and peer reviewed journal articles. The answers should have sufficient detail by describing relevant concepts, techniques and indices/measurements. Beware of including irrelevant information, such as generic description of existing theory. All statistical outputs should be presented within the report, however, relegate extensive tables to appendices.
The maximum word limit for the main assignment (excluding references, tables, contents page, footnotes, charts, graphs, figures) is 2000 words. The word count must be stated in the assignment cover sheet.
Markers will stop marking once the word count limit has been reached, likely leading to a reduced overall mark as key arguments or conclusions will not be included in the marked work.
Students who submit work that is below the word limit will not be penalised. This is because students will not have taken full advantage of the word limit available to them, which in itself may constitute a penalty.
The assignment should be in extended essay format (ie. use headings/sub-headings). Full academic referencing using the Harvard APA (6th Edition) referencing style should be used throughout the assignment. Guideline on how to reference using the APA style can be found at:
APA Referencing Short guide: http://tinyurl.com/pn9oaxt
APA Referencing Long Guide: http://tinyurl.com/bwdj2mk
To gain higher marks students are required to show analysis and reflection rather than simple description. They should use multiple sources of academic literature to frame and justify their analysis. All sources should be correctly identified – students are reminded the University enforces strict penalties for plagiarism (up to and including withdrawal from the University).
Correct English spelling and grammar should be used at all times. Assignments should be typed or word processed – hand-written assignments will not be accepted. Students who have been formally diagnosed with specific learning difficulties (SpLD) and assessed by the Disability Office should indicate ‘SpLD’ on the Student Declaration form included with their coursework submission.
Feedback Policy
Feedback on the coursework will be provided within three calendar weeks of submission. All feedback for the coursework assignment will be provided through GradeMark. Marks will be made available via Grade Centre in Blackboard and your university student portal. Please note that all marks are provisional until they have been ratified by a progression or award board and are therefore subject to change. Anonymous examples of good and bad practice will be shown in the final week of the module.
Avoiding Academic Misconduct
Academic misconduct is to commit any act where a student may obtain an unpermitted advantage for themselves or another. This can relate to any form of assessed work including:
A formal examination
A piece of coursework
Any form of assessment undertaken in pursuit of an academic or professional qualification at Swansea University.
Academic misconduct can be committed on an individual or group basis.
There are different types of academic misconduct including:
Plagiarism – defined as using, without acknowledgment, another person’s work and submitting it for assessment as though it were your own work; for instance, through copying or unacknowledged paraphrasing. This constitutes plagiarism whether it is intentional or unintentional.
Poor referencing can lead to you unintentionally plagiarising someone else’s work.
Collusion – defined as two or more students (or other persons) working together without prior authorisation in order to gain an unfair advantage, producing the same or similar piece of work and then attempting to present this work as entirely their own.
Commissioning – defined as the act of paying for, or arranging for another to produce, a piece of work which is then submitted for assessment as though it were the student’s own work
The University takes academic misconduct very seriously and it can have a detrimental effect on your results. In cases where academic misconduct is found to have taken place, it can result in one of the following:
The issue of a written reprimand and the text to be ignored when marking, resulting in a reduced mark
The cancellation of your mark for the assessment
The cancellation of your mark for the module concerned
In serious cases your marks for the entire year can be cancelled
Where can I find out more about Academic Misconduct?
You can access an online course via your Blackboard account.
The course can be found on a Blackboard site called ‘Academic Integrity’ found on the ‘My Studies’, listed under ‘My Organisations’ section. Following completion of the self-directed learning, there is a short online quiz, which will only take about 5 minutes to complete, to assess your level of understanding of the learning material. You can revisit the training material and retake the quiz as many times as you wish.
Full information on Academic Misconduct can be found at http://www.swansea.ac.uk/academic-services/academic-guide/assessment-and-progress/academic-misconduct-procedure/
Further advice and support is available from the Students’ Union Advice Centre, situated on the 1st floor of the Students’ Union building (Bay Campus) or the ground floor of Fulton House, just behind Costcutter and next to the stairs (Singleton Campus). You can email Advice@Swansea-union.co.uk or call 01792 295821.
2) Individual Coursework Assignment 2
This assignment is worth 50% of the overall module mark and consists of 2 parts (Part I and Part II).
Part I. Task Brief
For this coursework part I you are required to perform an Analysis of Variance using SPSS. Your solution should be word-processed and submitted electronically. Your solution should include any output produced from the analysis, and a detailed account of the methods you have used, the reasons you have chosen those particular methods, and the conclusions you have drawn.
The problem:
The data file Treatment costs, contains the treatment records of a sample of patients who received anti-clotting drugs during treatment for MI.
An experiment is carried out to determine the effect of using anti-clotting drugs and whether a patient is a smoker or not on the costs of treatment.
Load the data into SPSS and investigate the meaning of the values of the variables.
Perform a suitable two-way Analysis of Variance to investigate the results. If appropriate, include a suitable multiple comparisons analysis and/or a profile plot. Explain why it is appropriate to include (or exclude) such analyses.
You should address the following questions, explaining your answers in detail:
Are the main effects significant, and is there any significant interaction?
What percentage of the variation in the cost figures is accounted for by the model?
Is any particular type of anti-clotting drug significantly better or worse than the others in terms of treatment costs? If so, which one; and is it better or worse?
Do smokers or non-smokers have higher treatment costs?
If your requirement is to minimise treatment costs, which combination of drug type and smoking status would you select?
What type of anti-clotting drug makes the highest impact on treatment costs?
If your requirement is to minimise treatment costs, what other factors would you take into consideration, and what would you advise a patient?
Part II. Task Brief
For this coursework part II you are required to perform a correlation analysis and multiple regression using SPSS. Your solution should be word-processed and submitted electronically. Your solution should include any output produced from the analysis, and an account of the methods you used to obtain that output.
The problem:
Data: German credit.
In an investigation to determine how different factors affect the amount of credit issued to the credit applicants. Variables include Age of the applicant, number of available credits, and length of residence in the country of application.
Produce the Pearson correlation matrix for all variables except the name of the printer.
What are the two strongest relationships shown in the Pearson correlation matrix?
State in each case what the relationship is, and whether it is as one would expect.
If we are trying to model the relationship between Credit amount and the other variables, from these correlations, which variables should be considered for inclusion in the model?
SPSS offers a variety of methods (e.g. ‘Forwards’ ‘Backwards’ and ‘Stepwise’) for fitting regression models involving more than one predictor variable. Explain briefly the purpose of these methods.
Perform a Regression analysis to predict the “credit amount” variable from all the other numeric variables, using the “Enter” method.
What percentage of the variation in APR is accounted for by the four variables?
What are the null hypotheses tested by each of the sig values in your output? What conclusions should be drawn from these results?
Perform another Regression analysis to predict the “credit amount” variable from all the other numeric variables, using the “Backward” method.
Explain what has happened in the sequence of model fitting.
Using the final model in your output, on average what is the change in the applicant’s age when the credit amount is increased by one unit?
Using the final model, on average how much does the credit amount change by when there is a number of credits – 3, compared to number of credits – 2?
Looking at the excluded variables in the final model, are any of them “almost” included in the model? Explain your reasoning.
Key Marking criteria will include:
Accuracy of the calculations
Appropriateness of the methodology
Clarity and conciseness of the descriptions of the methodology
Word Limit
The word limit for this individual assignment is 2000 words.
The School of Management’s detailed word-limit policy, including the penalties relating to breaches of the specified word limit, are incorporated into the electronic cover sheet for coursework (available from the Assessment and Feedback folder on the Blackboard site for this module).
Submission
The full assignments must be submitted by 3pm on 10/04/2017 via Turnitin.
Please note:
The maximum file size that can be uploaded is 20mb. If your file is larger than this it is usually because you have included a lot of images – you should either remove some if possible, or else convert them to a more efficient format to bring the file size down (e.g. .png or .gif).
You should ensure your student number is in the title of the filename for the work you submit/upload.
The School of Management operates a late penalty system as follows: when work is submitted late with no prior authorisation, a penalty of 10% will be deducted from the actual mark for each calendar day, or part of a day, by which the deadline is exceeded. After seven days from the initial deadline, a mark of zero will be awarded. Late work should be submitted electronically in the usual way.
Digital Submission of Coursework Instructions
Logon to Blackboard.
Access the appropriate Module site.
Click the Assignment menu button which appears on the left of the screen.
In this folder you will see a file entitled ‘Student Declaration form’. You need to complete this form and incorporate it as the first page of your coursework (not two separate files).
Click Coursework. Please read the statement of originality before you click “submit”. By submitting work you are agreeing to this statement and confirming it to be true.
Complete the dialogue box with your forename and surname
To submit your coursework, locate the correct file on your computer by clicking the “browse” button and enter a title for the coursework (we suggest the module code and your student ID MNB108 123456). Click SUBMIT
You will then be asked to check if the document is the one you wish to submit and if so click “YES, SUBMIT”
You will then receive a message saying “paper successfully complete”.
BLACKBOARD will then send you a confirmation email of submission. Please keep this receipt safe as evidence of your submission.
If you experience any difficulties submitting your work via Turnitin please contact the Student Hub straight away.
Notes on Style & Word Count
The length limit for the assignment plan is one side of A4 paper. The text size should be 12 and the font Arial. The line spacing should be set to 1.2 as a minimum and the margins (all) should be a minimum of 1.9cm. References should be included on a separate page using the APA Harvard style of referencing.
This is a practical report, with an aim to present, analyse and describe your results, based on the task questions. The results should be interpreted with referencing to the relevant academic sources, such as textbooks and peer reviewed journal articles. The answers should have sufficient detail by describing relevant concepts, techniques and indices/measurements. Beware of including irrelevant information, such as generic description of existing theory. All statistical outputs should be presented within the report, however, relegate extensive tables to appendices.
The maximum word limit for the main assignment (excluding references, tables, contents page, footnotes, charts, graphs, figures) is 2000 words. The word count must be stated in the assignment cover sheet.
Markers will stop marking once the word count limit has been reached, likely leading to a reduced overall mark as key arguments or conclusions will not be included in the marked work.
Students who submit work that is below the word limit will not be penalised. This is because students will not have taken full advantage of the word limit available to them, which in itself may constitute a penalty.
The assignment should be in extended essay format (ie. use headings/sub-headings). Full academic referencing using the Harvard APA (6th Edition) referencing style should be used throughout the assignment. Guideline on how to reference using the APA style can be found at:
APA Referencing Short guide: http://tinyurl.com/pn9oaxt
APA Referencing Long Guide: http://tinyurl.com/bwdj2mk
To gain higher marks students are required to show analysis and reflection rather than simple description. They should use multiple sources of academic literature to frame and justify their analysis. All sources should be correctly identified – students are reminded the University enforces strict penalties for plagiarism (up to and including withdrawal from the University).
Correct English spelling and grammar should be used at all times. Assignments should be typed or word processed – hand-written assignments will not be accepted. Students who have been formally diagnosed with specific learning difficulties (SpLD) and assessed by the Disability Office should indicate ‘SpLD’ on the Student Declaration form included with their coursework submission.
Feedback Policy
Feedback on the coursework will be provided within three calendar weeks of submission. All feedback for the coursework assignment will be provided through GradeMark. Marks will be made available via Grade Centre in Blackboard and your university student portal. Please note that all marks are provisional until they have been ratified by a progression or award board and are therefore subject to change. Anonymous examples of good and bad practice will be shown in the final week of the module.
Avoiding Academic Misconduct
Academic misconduct is to commit any act where a student may obtain an unpermitted advantage for themselves or another. This can relate to any form of assessed work including:
A formal examination
A piece of coursework
Any form of assessment undertaken in pursuit of an academic or professional qualification at Swansea University.
Academic misconduct can be committed on an individual or group basis.
There are different types of academic misconduct including:
Plagiarism – defined as using, without acknowledgment, another person’s work and submitting it for assessment as though it were your own work; for instance, through copying or unacknowledged paraphrasing. This constitutes plagiarism whether it is intentional or unintentional.
Poor referencing can lead to you unintentionally plagiarising someone else’s work.
Collusion – defined as two or more students (or other persons) working together without prior authorisation in order to gain an unfair advantage, producing the same or similar piece of work and then attempting to present this work as entirely their own.
Commissioning – defined as the act of paying for, or arranging for another to produce, a piece of work which is then submitted for assessment as though it were the student’s own work
The University takes academic misconduct very seriously and it can have a detrimental effect on your results. In cases where academic misconduct is found to have taken place, it can result in one of the following:
The issue of a written reprimand and the text to be ignored when marking, resulting in a reduced mark
The cancellation of your mark for the assessment
The cancellation of your mark for the module concerned
In serious cases your marks for the entire year can be cancelled
Where can I find out more about Academic Misconduct?
You can access an online course via your Blackboard account.
The course can be found on a Blackboard site called ‘Academic Integrity’ found on the ‘My Studies’, listed under ‘My Organisations’ section. Following completion of the self-directed learning, there is a short online quiz, which will only take about 5 minutes to complete, to assess your level of understanding of the learning material. You can revisit the training material and retake the quiz as many times as you wish.
Full information on Academic Misconduct can be found at http://www.swansea.ac.uk/academic-services/academic-guide/assessment-and-progress/academic-misconduct-procedure/
Further advice and support is available from the Students’ Union Advice Centre, situated on the 1st floor of the Students’ Union building (Bay Campus) or the ground floor of Fulton House, just behind Costcutter and next to the stairs (Singleton Campus). You can email Advice@Swansea-union.co.uk or call 01792 295821.
School of Management
MN-2517 Statistics 2 for Business
Module Schedule
Week
Topic
Lecture Contents
Seminar Contents
Key Readings
1
Introduction
(i) Data input
Basic SPSS Practical
SPSS Survival Manual Chapters 6 & 7.
w/c
to SPSS
(ii) Organising data
6/2
(iii) Descriptive statistics
(iv) Graphs
2
Paired and
(i) Hypothesis testing
Implementation of paired
SPSS Survival Manual Chapter 17.
w/c
Two-Sample
(ii) Paired t-test
and two-sample t-tests in
13/2
t-tests
(iii) Levene’s Homogeneity of Variance test
SPSS
(iv) Two-Sample t-test
3
Correlation
(i) Pearson’s r
Implementation of
SPSS Survival Manual Chapter 11.
w/c
(ii) Positive/Negative Strong/Weak
Correlation Analysis in
20/2
Correlation
SPSS
(iii) Spearman’s Rank Correlation
4
Simple Linear
(i) Estimating the Regression Line
Simple Linear
SPSS Survival Manual Chapter 13.
w/c
Regression
(ii) The Regression ANOVA table
Regression in SPSS.
27/2
(iii) Confidence and Prediction Intervals
5
One-way
(i) One-way ANOVA
One-Way ANOVA and
SPSS Survival Manual Chapters 16 and 18.
w/c
ANOVA and
(ii) Post Hoc Multiple Comparisons: Tukey
Non-parametric
06/3
Non-
(iii) Unequal variances, Post Hoc Multiple
Statistics in SPSS
Parametric
Comparisons: Dunnett C.
Statistics
(iv) Non-parametric statistics: Mann-
Whitney, Kruskal-Wallis
6
Two-Way
(i) Two-Way ANOVA
Two-way ANOVA and
SPSS Survival Manual Chapter 19.
w/c
ANOVA with
(ii) Post Hoc Multiple Comparisons: Tukey
Interaction Plots in
13/3
and without
(iii) Interaction Plots
SPSS
interaction
Week
Topic
Lecture Contents
Seminar Contents
Key Readings
7
Cluster
(i) Hierarchical Cluster Analysis
Implementation of
w/c
Analysis
(ii) Icicle plots and dendrograms
Cluster Analysis in
20/3
(iii) Between group linkage
SPSS
(iv) The Agglomeration Schedule
8
Multiple
(i) Multiple Regression
Implementation of
w/c
Regression
(ii) Partial Regression Coefficients
Multiple Regression in
SPSS Survival Manual Chapter 13.
27/3
(iii) 3-D Scatterplot
SPSS
(iv) Regression diagnostics
(v) Forward and Backward Stepwise
Analysis
9
Factor
(i) Latent Variables
Implementation of
SPSS Survival Manual Chapter 15.
w/c
Analysis
(ii) R-Matrix
Exploratory Factor
3/4
(iii) Factor Extraction
Analysis in SPSS
10
Introduction
(i) Introduction to AMOS
Implementation of CFA
w/c
to AMOS
(ii) CFA
and SEM in AMOS
1/5
(iii) SEM
G E N E R I C M A R K I N G P R O G R A M M E
§ Mark (%) Class [Descriptor]
§ Information and knowledge
§ Application
§ Analysis
§ Synthesis and context
Evaluation
§ 80-100
First
[Outstanding]
Contains all information required, with no errors. Evidence of study beyond the module content.
Answers question fully and completely. Excellent adaptation and application of concepts. No irrelevant material.
Ideas expressed logically and coherently. Excellent use of appropriate mathematical / diagrammatic exposition.
Excellent integration of ideas and information. Demonstrates outstanding understanding of topic within a wider context.
Shows evidence of significant independent thinking and critical awareness, and
originality.
§ 70-79
First
[Excellent]
Contains all information required, with no major errors and no or very few minor errors.
Answers question fully and completely. Good adaptation and application of concepts. Little or no irrelevant material.
Ideas expressed logically and coherently. Effective use of appropriate mathematical / diagrammatic exposition.
Effective integration of ideas and information. Demonstrates substantial understanding of topic within a wider context.
Shows evidence of sound independent thinking and critical awareness.
§ 60-69
Upper second
[Very good]
Contains all or almost all information required, with no major errors and only a few minor errors.
Answers question fully. Some adaptation and application of concepts. Little or no irrelevant material.
Ideas generally expressed logically and coherently. Competent use of appropriate mathematical / diagrammatic exposition.
Competent integration of ideas and information. Demonstrates some understanding of topic within a wider context.
Shows some evidence of independent thinking and critical awareness.
§ 50-59
Lower second
[Good]
Contains most information required, with no or very few major errors and some minor errors.
Partially answers question. Limited adaptation and application of concepts. Some irrelevant material.
Ideas not always expressed logically and coherently. Adequate use of appropriate mathematical / diagrammatic exposition.
Limited integration of ideas and information. Demonstrates modest but incomplete understanding of topic and its context.
Shows little evidence of independent thinking and critical awareness.
§ 40-49
Third
[Satisfactory]
Contains basic (core) information required, with some major and minor errors.
Only answers some aspects of question. No adaptation or application of concepts. Some irrelevant material.
Ideas rarely expressed logically and coherently. Limited use of appropriate mathematical expressions.
Minimal integration of ideas and information. Demonstrates limited understanding of topic and its context.
Shows very little or no evidence of independent thinking and critical
§ 30-39
Fail (Potentially tolerable) [Poor]
Contains only a limited amount of information required, with numerous major and minor errors.
Does not answer question. No adaptation or application of concepts. Much irrelevant material.
Ideas rarely expressed logically and coherently. Little or no use of appropriate mathematical / diagrammatic exposition.
No integration of ideas and information. Demonstrates little understanding of topic and its context.
Shows no evidence of independent thinking or critical awareness.
§ 0-29
Fail (Not tolerable) [Very poor]
Contains none or almost none of information required and with many major and minor errors.
Wholly fails to answer question. No adaptation or application of concepts. Largely irrelevant material.
Ideas expressed incoherently. No linking of ideas within text. Little or no use of appropriate mathematical / diagrammatic exposition.
No integration of ideas and information. Demonstrates no understanding of topic and its context.
Shows no evidence of independent thinking or critical awareness.
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We keep the quality bar of all papers high. But in case you need some extra brilliance to the paper, here’s what to do. First of all, you can choose a top writer. It means that we will assign an expert with a degree in your subject. And secondly, you can rely on our editing services. Our editors will revise your papers, checking whether or not they comply with high standards of academic writing. In addition, editing entails adjusting content if it’s off the topic, adding more sources, refining the language style, and making sure the referencing style is followed. -
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We make sure that clients’ personal data remains confidential and is not exploited for any purposes beyond those related to our services. We only ask you to provide us with the information that is required to produce the paper according to your writing needs. Please note that the payment info is protected as well. Feel free to refer to the support team for more information about our payment methods. The fact that you used our service is kept secret due to the advanced security standards. So, you can be sure that no one will find out that you got a paper from our writing service. -
Money Back Guarantee
If the writer doesn’t address all the questions on your assignment brief or the delivered paper appears to be off the topic, you can ask for a refund. Or, if it is applicable, you can opt in for free revision within 14-30 days, depending on your paper’s length. The revision or refund request should be sent within 14 days after delivery. The customer gets 100% money-back in case they haven't downloaded the paper. All approved refunds will be returned to the customer’s credit card or Bonus Balance in a form of store credit. Take a note that we will send an extra compensation if the customers goes with a store credit. -
24/7 Customer Support
We have a support team working 24/7 ready to give your issue concerning the order their immediate attention. If you have any questions about the ordering process, communication with the writer, payment options, feel free to join live chat. Be sure to get a fast response. They can also give you the exact price quote, taking into account the timing, desired academic level of the paper, and the number of pages.