Business Data Analysis assignment description and requirements

Task 1. Personal Insights COVID-19 Coronavirus Pandemic:

The learning outcomes for the HDSDA Business Data Analysis Module include the development of proficiency in the following:

• The principles and uses of descriptive statistics and inferential statistics.
• Principles of statistical Inquiry
• Analyses based on descriptive and inferential statistics within a business context
• Use of methodologies applied in prediction (forecasting)

Using the context of the current COVID-19 Coronavirus Pandemic as a basis, discuss and give examples and descriptions of how the personal skills and competencies associated with these learning outcomes are relevant to your personal technical analysis, appreciation, and understanding of the issues related to. and impacts resulting from, the global pandemic.

You should take as comprehensive a view as possible of all the possible aspects of the current pandemic crisis using the topics covered in the module as a primary basis of your consideration.

Note: This is intended as a discussion exercise only based on your own personal insights into the concepts involved. You should focus on your own personal learning and understanding rather than the real accuracy of any reports or data. There is no requirement to source or use actual data or to provide actual factual examples, but you could use illustrative diagrams/graphs where appropriate in your descriptions if you wish.

Task 2. Are apartment rents significantly different in the four regional Irish cities?

Source average monthly rents for two-bed apartments by quarter for the 10 years to Q3 2019 from the Residential Property Board (RTB) data held on the Central Statistics Office Statistic Bank (https://statbank.cso.ie). Based on the second last digit of your student number, as outlined below, use a subset of this quarterly data as samples of rents for input to a comparison of mean rents in three of the four cities (i.e. the data for three of the fours datasets for Cork City, Galway City, Limerick City and Waterford City) – selecting cities based on your Student Number as shown below.

1. Specify the null and alternate hypotheses to determine if there is a significant difference between the mean rents in the three cities.
2. Using the two-bed apartment quarterly rent data for the three selected cities, calculate the test statistic to test your hypotheses and report your result.

• Report your overall outcome, clearly explain your reason for choosing this particular statistical test, your reasoning behind the process you followed, any decisions you made and any limitations on the outcome.

NOTE: You should carry out and clearly present all your calculations in Excel showing both the ‘manual’ step by step process and also the solution output derived using the Data Analysis Excel tool-pack.

Datasets to use based on the last two digits of your Student Number (S/N)

Example:  Student Number x12345678, use next 20 quarters starting with and including 2013 Q3 [7] and compare the rent data for Cork City, Limerick City and Waterford City [8].

Task 3: Central Statistics Office Data and Building Activity

The ‘Production in Building and Construction Index’ figures given in the Central Statistics Office data gives an indication of the level of recent Building and Construction activity in Ireland. Source the exact dataset indicated by your own Student Number (S/N) for Value or Volume of Production, and for the correct quarters indicated below.

Assuming the estimated index figure for the first relevant quarter in 2015 was 100.00 ((i.e. for Q1 2015 or Q2 2015 based on your S/N), using three different methods, make three individual forecasts of the next index figure for next relevant quarter in 2020 (i.e. for Q1 2020 or Q2 2020 based on your S/N). Compare and explain your three forecast figures.

Note: you should lay out your data and calculations clearly in Excel. Where needed: use six periods for averaging calculations, weightings of 5 (most recent), 4, 3, 2, 1 and 0.5 (t – 6) and an alpha value of 0.4.

Datasets to use based on two digits of your Student Number (S/N)

Example:  Student Number x12345678, use Table 1(a), Volume of Production [5] and only quarters Q1 and Q3 figures for each year.[6]

Task 4. Central Statistics Office Data continued

Figures for the Residential Property Price Index, adjusted to a baseline of 100 in Q1 2015 are as follows:

2015	Q1	100.00
	Q2	103.62
	Q3	106.08
	Q4	106.73
2016	Q1	107.37
	Q2	109.31
	Q3	114.62
	Q4	116.30
2017	Q1	117.85
	Q2	121.73
	Q3	128.33
	Q4	130.40
2018	Q1	132.73
	Q2	136.22
	Q3	139.20
	Q4	138.55
2019	Q1	137.77
	Q2	138.94
	Q3	140.75
	Q4	139.20

Using the dataset for the element of the ‘Production in Building and Construction Index’you sourced in Task 3 above and extracting the relevant data above for the same quarters you used in Task 3, produce in Excel a scatter plot of your element of the ‘Production in Building and Construction Index’(x-axis) against the extracted figures for the  ‘Residential Property Price Index’ for the appropriate quarters of 2015 to 2019 with the trendline equation and R-squared value shown on the chart.

What can you tell about the relationship between these two variables?