Primary data simply means the data from the original source with the purpose in mind. It is the kind of data that has not been distorted by a third party unlike the secondary data that can be described as the kind of data that has been collected by any other user apart from the original user. Examples of primary data include photographs from cameramen while data used for census reasons forms a great example of some of the citations of secondary data.
Topic 1: Examples of Primary Data
In the analysis of the House of Commons European Union results on the Brexit referendum in 2016, there is an analysis of the results of the referendum showing that at least 17,410,742 of the 33,577,342 cast votes voted for the exit from the European Union against 16,141,241 voters that voted for the status quo representing 48.1% of the votes cast. This is official data from the parliament of the United Kingdom. It is the best example of primary data as it is not data derived from the secondary source. In this scenario, such kind of data has got various advantages and disadvantages. The advantages include the fact that by search kind of data having found its way into the statistics of the day, it means that that data has been used before in numerous situations and statistics thus making that data to be reliable for further research and testimonials. However, there are many possibilities that relying on such kind of data is exposing us to an out-dated data that may not be helpful in resolving present situations.
Joseph Rowntree Foundation’s report dubbed “ Brexit vote explained: poverty, low skills and lack of opportunities” conducted by Mathew Godween, best explains the example of how primary data can be. Primary data best illustrates the condition in its original situation. In the report, Godween observes that the poorest households in Britain with an annual income of less than 20,000 pounds per year were more likely to vote for Brexit as compared to those with higher incomes. Additionally, he reported that those groups that were vulnerable to poverty in the Great Britain were more likely to vote for Brexit as compared to the privileged ones in the same country. This is the primary data of information by mere fact that it is original as it is being told by someone who is on the ground doing his research and statistics. One beauty of the primary data is the fact that it is reliable and original as it has not been distorted by the second and third party as the case with secondary data.
Topic 2: Examples of Secondary Data
The Centre for Social Justice Report by Legatum Institute is another example of secondary data. In the report, the Centre highlights the reasons that led to Britain exiting from the European Union including the general economy, security issues, and sovereignty of the Great Britain among other reasons. Just like other examples of the demerits of secondary data, this source of information from the Centre for Social Justice is less costly as compared as compared to the primary source of data.
The BBC’s report called “Local voting figures shed new light on EU referendum” by Martin Rosenbaum is another classic example of secondary data. The author relies on past articles and statistics to present a very credible report. This type of data is quite efficient and effective in the sense that by the fact that it has been used before in producing makes it quite reliable to base on it.
The last example of secondary data is a report by Lord Ashcroft dubbed “How the United Kingdom voted… and why.” He also gives a secondary account of the voting pattern of the United Kingdom in the Brexit vote. By analysing and looking closely at his figures, you realize the effectiveness of his secondary report being that his data has a degree of reliability and validity thus can be used in future studies and analysis.
Topic 3: Interpretation of Data Reports from ONS by Various Independent Report Outlets
The report of British population projections from the Office for National Statistics has various presentations of the factual data from different sources. While the Office of National Statistics reports that the population will be increasing at an average of 5.5% with England experiencing most of the growth, the Daily Mail quotes Office of National Statistics saying the population growth will be slowing down. However, the paper rightly quotes the projections in international migrations in the following 10 years as rightly quoted by the Office of National Statistics to be 54%.
The BBC’s report regarding the Office of National Statistics is apt. It rightly captures the population projections for the next decade to pass the 70m mark as reported by the Office. BBC’s report in terms of the population growth is also in tandem with the Office of National Statistics as it puts it at 5.5%. The same applies to the Breitbart firm who rightly quotes the Office of the National Statistics as having projected 46% of the population growth to be as a result of the occurrence of more births than deaths. Finally, OBR also resonates with the population projections of the statistics firm. Just like in the National Statistics Department report, there are reported cases of increase in migration for children under the age of fifteen between the years 2021-2022 despite the decrease in births during the period. However, for the age of between 16-50 years, there is a decrease in population for this group thus best capturing the decrease in migration for this group into the United Kingdom. Finally, just as it was captured by the Office of National statistics, there is an increase in population of people aged 51 years and above from the year 2022 as a result of the higher net migration. This secondary information from OBR truly reflects the primary information from the Office of the National Statistics that it had been sourced from.
Topic 4 – Graphs, Charts and Pivot Tables.
US Presidential Election 2016
The graph above shows the nationwide popular votes for all candidates listed on at least one state ballot including those for minor parties. The minor parties exclusive of the first 5 candidates are represented by the others
as labelled on the graph.
The graph (Electoral and Popular vote) above shows the popular votes for the two main candidates in each state, and also how the Electoral College votes for each state as distributed.
Crypto-Currencies Exchange Rates Price data.
Computer Memory Prices 1957-2017
Create a table of values and a graph showing the values of f(z) for this function:
Z
-3
-2.9
-2.8
-2.7
-2.6
-2.5
-2.4
-2.3
-2.2
-2.1
-2
-1.9
-1.8
-1.7
-1.6
-1.5
-1.4
-1.3
-1.2
-1.1
-1
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
1.52656E-15
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3
f(z)
0.42
0.42
0.43
0.43
0.43
0.43
0.44
0.44
0.44
0.45
0.45
0.46
0.47
0.47
0.48
0.50
0.51
0.54
0.56
0.60
0.66
0.74
0.87
1.11
1.60
2.95
9.08
103.19
107051.09
2068398244706260000000.00
#NUM!
2068398244699960000000.00
107051.09
103.19
9.08
2.95
1.60
1.11
0.87
0.74
0.66
0.60
0.56
0.54
0.51
0.50
0.48
0.47
0.47
0.46
0.45
0.45
0.44
0.44
0.44
0.43
0.43
0.43
0.43
0.42
0.42
Topic 6 Hypothesis Tests
The following is an output from a t-test computation using Microsoft Excel based on the data given.
t-Test: One-Sample
Daily Output
Mean
86
Variance
51.78
Observations
16
Hypothesized Mean
90
Df
15
t Stat
-2.223509348
P(T<=t) one-tail
0.020983354
t Critical one-tail
1.753050356
P(T<=t) two-tail
0.041966707
t Critical two-tail
2.131449546
From the output, the mean after modifying the manufacturing process is 86. This is less than the mean before modifying the process as according to the result of the t-test. Therefore from the data, a change has been observed in the mean of the daily output of the manufacturing process.
The p-value for the one-tailed t-test is 0.02098.
Topic 7 - Correlation and Regression
The graph shows the relationship between the price and consumption of petrol from the period 1990- 2015 as generated using Excel. The equation of the straight line of best fit as displayed on the graph generated as well as the R2 also displayed. The table below shows the slope, the correlation coefficient R and the intercept of the straight line of best fit as obtained by the excel functions: SLOPE, CORREL, and INTERCEPT respectively.
The R2
value is obtained by squaring the Correlation coefficient value as computed bellow:
Slope
-0.1
Correlation
-0.96416
R2
0.929604
Intercept
29.71464
Comparison of the results
When we compare the results displayed on the chart with the results obtained using the SLOPE, INTECEPT and CORREL functions in Excel, values of the computation methods are same only that the decimals and rounding off which may result in a minor difference if the two models are used to predict the variables. The value of R2 computed is the same as the generated value from the graph.
From the straight line model, price of petrol accounts for 92.96% of consumption of petrol while 7.04% is accounted by other factors.
Topic 8 – Forecasting
By observing the consumption trend-line, the predicted four quarters of 2018 will have a constant value. This is proved using the FORECAST function in excel resulting in a predicted value for domestic gas consumption to be 76,525 for the quarters.
