Data Analysis on how has Brexit affected workforce from the EEU on example of Polish, Romanian and Spain migrants
Budget: £20 – £250 GBP
Format - report
2000 Words
Cover page
Table of contents – generated by the Word Tools
Introduction Project Aim – what you intend to achieve
Objectives – what you plan to do to achieve the aim
Detail the group overall but focus on what you contributed to the project, your methodology
Where did you get the data from?
How appropriate is the data, ensure you reference sources for the data.
What analysis did you perform?
Discuss how your method of presenting and visualising the data is appropriate
What did you achieve and what conclusions did you draw?
How did the group function together and how in future might you work differently
Discuss any issues you had and what in the future you might do differently.
Conclusion
Appropriate references for where each of the datasets came from and any other referenced material
Page 2 - Table of Contents.
Last page – references.
Note:
• Use Times New Roman, 12 normal fonts.
• 1.5 single spacing.
• Numbered the pages (at the bottom centre) except for the Cover Page.
• Appropriate Harvard referencing. Footnotes may be used to direct readers to appropriate appendices
Instructions:
1. look at data available from the ONS, Office of National Statistics. For something more international the World Data Bank has vast open datasets you could consider.
2. work for this should be submitted in a word document and must include all relevant output from Excel
3. explore, analyse and interpret the output.
4. Choose one or two of the models below that will be used in the report
5. perform relevant analyses on chosen dataset and include the results in your report.
6. demonstrate a good understanding of the key data analysis concepts, such as probability, correlation, regression, time series analysis, forecasting, box and whisker plot and importance of visualization.
Please bear the following points in mind:
a). If you use simple linear regression analysis with one independent variable, your answers should include the following in the context of the problem.
- graphical presentation (scatter diagram)
- regression equation,
- interpretation of correlation coefficient, coefficient of determination,
- interpretation of y-intercept, the slope (gradient)
- comment on the P-values test
- your conclusion of the regression model.
b) If you use multiple linear regression analysis with more than one independent variables, your answers should include the following in the context of the problem.
- graphical presentation (scatter diagram) of the dependent variables with each
independent variables
- regression equation,
- interpretation of correlation coefficient, coefficient of determination,
- interpretation of y-intercept, and all the slopes (gradients)
- comment on the P-values test
- your conclusion of the regression model.
c) For forecasting analysis, using time series data:
- Construct a time-series plot for this data set.
- Describe any trend and seasonal behavior that you can see in the plot.
- Compute seasonal indices using moving (MA) average followed by a centre moving average (CMA).
- Obtain forecast for the next three quarters.
d) If you use Dashboard Analysis to answer business key indicators performance, then fellow all the steps and the functionality that was introduce in the lecture (i.e., Excel Class Example)
More materials on request.
2000 Words
Cover page
Table of contents – generated by the Word Tools
Introduction Project Aim – what you intend to achieve
Objectives – what you plan to do to achieve the aim
Detail the group overall but focus on what you contributed to the project, your methodology
Where did you get the data from?
How appropriate is the data, ensure you reference sources for the data.
What analysis did you perform?
Discuss how your method of presenting and visualising the data is appropriate
What did you achieve and what conclusions did you draw?
How did the group function together and how in future might you work differently
Discuss any issues you had and what in the future you might do differently.
Conclusion
Appropriate references for where each of the datasets came from and any other referenced material
Page 2 - Table of Contents.
Last page – references.
Note:
• Use Times New Roman, 12 normal fonts.
• 1.5 single spacing.
• Numbered the pages (at the bottom centre) except for the Cover Page.
• Appropriate Harvard referencing. Footnotes may be used to direct readers to appropriate appendices
Instructions:
1. look at data available from the ONS, Office of National Statistics. For something more international the World Data Bank has vast open datasets you could consider.
2. work for this should be submitted in a word document and must include all relevant output from Excel
3. explore, analyse and interpret the output.
4. Choose one or two of the models below that will be used in the report
5. perform relevant analyses on chosen dataset and include the results in your report.
6. demonstrate a good understanding of the key data analysis concepts, such as probability, correlation, regression, time series analysis, forecasting, box and whisker plot and importance of visualization.
Please bear the following points in mind:
a). If you use simple linear regression analysis with one independent variable, your answers should include the following in the context of the problem.
- graphical presentation (scatter diagram)
- regression equation,
- interpretation of correlation coefficient, coefficient of determination,
- interpretation of y-intercept, the slope (gradient)
- comment on the P-values test
- your conclusion of the regression model.
b) If you use multiple linear regression analysis with more than one independent variables, your answers should include the following in the context of the problem.
- graphical presentation (scatter diagram) of the dependent variables with each
independent variables
- regression equation,
- interpretation of correlation coefficient, coefficient of determination,
- interpretation of y-intercept, and all the slopes (gradients)
- comment on the P-values test
- your conclusion of the regression model.
c) For forecasting analysis, using time series data:
- Construct a time-series plot for this data set.
- Describe any trend and seasonal behavior that you can see in the plot.
- Compute seasonal indices using moving (MA) average followed by a centre moving average (CMA).
- Obtain forecast for the next three quarters.
d) If you use Dashboard Analysis to answer business key indicators performance, then fellow all the steps and the functionality that was introduce in the lecture (i.e., Excel Class Example)
More materials on request.