What should you do to write a good academic answer after analysing your data?

You need to complete ONLY part 1.1 and 1.2 of the Measuring climate change Empirical Project using Excel. The link provides all the instruction you need to complete the project. To access the link, you will need to sign up to the CORE ECON project. To complete the project, you will need to apply your research skills developed in Economics I, read and understand Units 1 (which you already covered in Economics I). Reading Unit 20 (last topic covered in Economics II) can be of help but is not compulsory. You are to do ONLY part 1.1 and 1.2 of the empirical project, with the following slight changes.Part 1.1 The behaviour of average surface temperature over time • Instead of the instructions in question 2 given in the empirical project, follow these instructions. ‘Select the month you were born and plot a line chart with average temperature anomaly on the vertical axis and time from 1880 to 2021 on the horizontal axis. Label each axis appropri- ately and give your chart a suitable title.’ • For question 3 and 4, instead of ‘…(from 1880 to the latest year available)…’, given in the empirical project, use ‘from 1880 to 2021’. – For D-N, DJF, the 1880 data is missing, so use data from 1881 to 2021. No need to explain this in a footnote since it applies to everyone. 2. Part 1.2 Variation in temperature over time • Question 1 and remaining questions, instead of the instructions given in the empirical project, the second frequency table should be from 1981 to 2021, not 2010. • For Figure 1.5 in question 1, the first column of the table should range from -0.3 to 1.25 to also count values between 1.05 and 1.10, 1.10 and 1.15, and 1.15 and 1.20, and 1.20 and 1.25. • Question 3, calculate the 3rd and 7th decile also using the 1981- 2021 period. What should you do to write a good academic answer after analysing your data? • A good academic answer would show that you have done additional research beyond the reading materials in the module (including CORE the economy and articles in the empirical project) to demonstrate you have understood the significance of climate change. For example pro- viding GISTEMP Team (2022) as the only reference does not demon- 2 strate additional research beyond the module materials and you will not get marks for this criteria which affects your overall grade. • You are expected to conduct your own research in order to provide detailed background information why climate change is important. • Ensure to cite all the relevant sources that you read. • Again, you are also expected to use the tools and skills learned in Economics I and Economics II to complete this empirical project. These are not full attachments, I will send more details. In the questions below, we look at data from NASA about land-ocean temperature anomalies in the northern hemisphere. Figure 1.1 is constructed using this data, and shows temperatures in the northern hemisphere over the period 1880–2016, expressed as differences from the average temperature from 1951 to 1980. We start by creating charts similar to Figure 1.1, in order to visualize the data and spot patterns more easily.Before plotting any charts, download the data and make sure you understand how temperature is measured: Go to NASA’s Goddard Institute for Space Studies website. Under the subheading ‘Combined Land-Surface Air and Sea-Surface Water Temperature Anomalies’, select the CSV version of ‘Northern Hemisphere-mean monthly, seasonal, and annual means’ (right-click and select ‘Save Link As…’). The default name of this file is NH.Ts+dSST.csv. Give it a suitable name and save it in an easily accessible location, such as a folder on your Desktop or in your personal folder. In this dataset, temperature is measured as ‘anomalies’ rather than absolute temperature. Using NASA’s Frequently Asked Questions section as a reference, explain in your own words what temperature ‘anomalies’ means. Why have researchers chosen this particular measure over other measures (such as absolute temperature)? Now create some line charts using monthly, seasonal, and annual data, which help us look for general patterns over time. Choose one month and plot a line chart with average temperature anomaly on the vertical axis and time (from 1880 to the latest year available) on the horizontal axis. Label each axis appropriately and give your chart a suitable title (Refer to Figure 1.1 as an example.) Drawing a line chart of temperature and time The data : This is what the temperature data looks like. Column A has time (in years), Column B has temperature deviations, and Column C contains the average northern hemisphere temperature. We will be using Columns A and B to make the line chart. Draw a line chart : After completing step 4, your line chart will look similar to this. Temperature deviation is on the vertical axis and time is on the horizontal axis. Notice that the numbers for time are not correct (they should be years). Change the horizontal axis variable to years : To change the horizontal axis labels to years, we need to add the values in Column A to the line chart. Change the horizontal axis variable to years : The current horizontal axis labels are the numbers 1, 2, 3, and so on. To change these labels to years, we need to edit the labels. Change the horizontal axis variable to years : After completing step 10, the horizontal axis will be in time (years). Reposition the horizontal axis : After completing step 12, the horizontal axis will be at the bottom of the chart. Add titles : Give the axes and the chart appropriate titles. The data : This is what the temperature data looks like. Column A has time (in years), Column B has temperature deviations, and Column C contains the average northern hemisphere temperature. We will be using Columns A and B to make the line chart. The data This is what the temperature data looks like. Column A has time (in years), Column B has temperature deviations, and Column C contains the average northern hemisphere temperature. We will be using Columns A and B to make the line chart. Draw a line chart : After completing step 4, your line chart will look similar to this. Temperature deviation is on the vertical axis and time is on the horizontal axis. Notice that the numbers for time are not correct (they should be years). Draw a line chart After completing step 4, your line chart will look similar to this. Temperature deviation is on the vertical axis and time is on the horizontal axis. Notice that the numbers for time are not correct (they should be years). Change the horizontal axis variable to years : To change the horizontal axis labels to years, we need to add the values in Column A to the line chart. Change the horizontal axis variable to years To change the horizontal axis labels to years, we need to add the values in Column A to the line chart. Change the horizontal axis variable to years : The current horizontal axis labels are the numbers 1, 2, 3, and so on. To change these labels to years, we need to edit the labels. Change the horizontal axis variable to years The current horizontal axis labels are the numbers 1, 2, 3, and so on. To change these labels to years, we need to edit the labels. Change the horizontal axis variable to years : After completing step 10, the horizontal axis will be in time (years). Change the horizontal axis variable to years After completing step 10, the horizontal axis will be in time (years). Reposition the horizontal axis : After completing step 12, the horizontal axis will be at the bottom of the chart. Reposition the horizontal axis After completing step 12, the horizontal axis will be at the bottom of the chart. Add titles : Give the axes and the chart appropriate titles. Add titles Give the axes and the chart appropriate titles. Figure 1.2 How to draw a line chart of temperature and time. Extra practice: The columns labelled ‘DJF’, ‘MAM’, ‘JJA’, and ‘SON’ contain seasonal averages (means). For example, the ‘MAM’ column contains the average of the March, April, and May columns for each year. Plot a separate line chart for each season, using average temperature anomaly for that season on the vertical axis and time (from 1880 to the latest year available) on the horizontal axis. The column labelled ‘J–D’ contains the average temperature anomaly for each year. Plot a line chart with annual average temperature anomaly on the vertical axis and time (from 1880 to the latest year available) on the horizontal axis. Your chart should look like Figure 1.1. Extension: Add a horizontal line that intersects the vertical axis at 0, and label it ‘1951–1980 average’. What do your charts from Questions 2 to 4(a) suggest about the relationship between temperature and time? You now have charts for three different time intervals: month (Question 2), season (Question 3), and year (Question 4). For each time interval, discuss what we can learn about patterns in temperature over time that we might not be able to learn from the charts of other time intervals. Compare your chart from Question 4 to Figure 1.4 which also shows the behaviour of temperature over time using data taken from the National Academy of Sciences. Discuss the similarities and differences between the charts. (For example, are the horizontal and vertical axes variables the same, or do the lines have the same shape?) Looking at the behaviour of temperature over time from 1000 to 1900 in Figure 1.4, are the observed patterns in your chart unusual? Based on your answers to Questions 4 and 5, do you think the government should be concerned about climate change? Aside from changes in the mean temperature, the government is also worried that climate change will result in more frequent extreme weather events. The island has experienced a few major storms and severe heat waves in the past, both of which caused serious damage and disruption to economic activity. Will weather become more extreme and vary more as a result of climate change? A New York Times article uses the same temperature dataset you have been using to investigate the distribution of temperatures and temperature variability over time. Read through the article, paying close attention to the descriptions of the temperature distributions. We can use the mean and median to describe distributions, and we can use deciles to describe parts of distributions. To visualize distributions, we can use column charts in Excel. (For some practice on using these concepts and creating column charts in Excel, see Section 1.3 of Economy, Society, and Public Policy). We are now going to create similar charts of temperature distributions to the ones in the New York Times article, and look at different ways of summarizing distributions. In order to create a column chart using the temperature data we have, we first need to summarize the data using a frequency tablefrequency table A record of how many observations in a dataset have a particular value, range of values, or belong to a particular category.close. Instead of using deciles to group the data, we use intervals of 0.05, so that temperature anomalies with a value from -0.3 to -0.25 will be in one group, a value greater than -0.25 up until 0.2 in another group, and so on. The frequency table shows us how many values belong to a particular group. Using the monthly data for June, July, and August (columns G to I in your spreadsheet), create two frequency tables similar to Figure 1.5 for the years 1951–1980 and 1981–2010, respectively. The values in the first column should range from -0.3 to 1.05, in intervals of 0.05.