update assignments link. simplified all links.

_freeze/assignments/A1/execute-results/html.json

@@ -2,7 +2,7 @@
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   "result": {
     "engine": "knitr",
-    "markdown": "---\ntitle: Individual Assignment 1 (5%)\n---\n\n\n\n**You must provide forecasts for the following items:**\n\n  1. Google closing stock price on 21 March 2025 [[Data](https://finance.yahoo.com/quote/GOOG/)].\n  2. Maximum temperature at Melbourne airport on 11 April 2025 [[Data](http://www.bom.gov.au/climate/dwo/IDCJDW3049.latest.shtml)].\n  3. The difference in points (Collingwood minus Essendon) scored in the AFL match between Collingwood and Essendon for the Anzac Day clash. 25 April 2025 [[Data](https://en.wikipedia.org/wiki/Anzac_Day_match)].\n  4. The seasonally adjusted estimate of total employment for April 2025 in ('000). ABS CAT 6202, to be released around mid May 2025 [[Data](https://www.abs.gov.au/statistics/labour/employment-and-unemployment/labour-force-australia/latest-release)].\n  5. Google closing stock price on 23 May 2025 [[Data](https://finance.yahoo.com/quote/GOOG/)].\n\nFor each of these, give a **point forecast** and an **80% prediction interval**, and **explain in a couple of sentences** how each was obtained.\n\n* Prepare short justifications with your forecasts and forecast intervals explaining in no more than 50-70 words how these were obtained. Only a couple of sentences are required. There is no need to use any fancy models or sophisticated methods. \n* **Full marks will be awarded** if you submit the required information, and are able to meaningfully justify your results in a couple of sentences in each case. \n\n### Submission\n\nYour forecasts should be submitted in moodle by **9.30am, on Monday, March 10**.\n\n\n\n\n\n<br><br><hr><b>Due: 10 March 2025</b><br><a href=https://learning.monash.edu/mod/quiz/view.php?id=3877918 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF5231)</b>&nbsp;&nbsp;</font><br></a><br><br><hr><b>Due: 10 March 2025</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=3877940 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF3231)</b>&nbsp;&nbsp;</font><br></a>\n\n\n\n\n\n\n\n#### Tips\n\n* The [Data] links give you possible data to start with, but you are free to use any data you like.\n* There is no need to use any fancy models or sophisticated methods. Simple is better for this assignment. The methods you use should be understandable to any high school student.\n\n## Forecasting competition\n\nOnce the true values in each case are available, we will come back to this exercise and see who did the best using the scoring method described in class. The student with the best score will be the winner of our forecasting competition (something really nice to have on your CV), and will also win a $100 Amazon gift voucher.\n\nNote: your assignment mark is not dependent at all on the score you obtain in the competition.\n\n\n### Scoring \n\\small\n\nLet $y=$ actual, $\\hat{y}=$ point forecast, $[\\hat{\\ell},\\hat{u}]=$ prediction interval\n\n#### Point forecasts:\n\n$$\\text{Absolute Error} = |y-\\hat{y}|$$\n\n\\vspace{-0.4cm}\n\n * Rank results for all students in class\n * Add ranks across all five items\n\n#### Prediction intervals:\n\n$$\n\\text{Interval Score} = (\\hat u - \\hat\\ell) + 10(\\hat\\ell - y)_+ + 10 (y-\\hat u)_+\n$$\n\n\\vspace{-0.5cm}\n\n* $u_+=max(u,0)$\n* Rank results for all students\n* Add ranks across all five items\n\n\n<!-- ### Submitted forecasts -->\n\n<!-- * [Q1](Q1.png); [Q1-zoom](Q1zoom.png). -->\n<!-- * [Q2](Q2.png); [Q2-zoom](Q2zoom.png). -->\n<!-- * [Q3](Q3.png); [Q3-zoom](Q3zoom.png). -->\n<!-- * [Q4](Q4.png); [Q4-zoom](Q4zoom.png). -->\n\n<!-- ### Leaderboard -->\n\n<!-- <iframe src=\"https://docs.google.com/spreadsheets/d/1_3RcdspMIL7TIaD7566bEbUEe8LHcg4UNQS1-ex-NZg/edit?usp=sharing\" width = \"110%\" height = 500></iframe> -->\n\n",
+    "markdown": "---\ntitle: Individual Assignment 1 (5%)\n---\n\n\n\n**You must provide forecasts for the following items:**\n\n  1. Google closing stock price on 21 March 2025 [[Data](https://finance.yahoo.com/quote/GOOG/)].\n  2. Maximum temperature at Melbourne airport on 11 April 2025 [[Data](http://www.bom.gov.au/climate/dwo/IDCJDW3049.latest.shtml)].\n  3. The difference in points (Collingwood minus Essendon) scored in the AFL match between Collingwood and Essendon for the Anzac Day clash. 25 April 2025 [[Data](https://en.wikipedia.org/wiki/Anzac_Day_match)].\n  4. The seasonally adjusted estimate of total employment for April 2025 in ('000). ABS CAT 6202, to be released around mid May 2025 [[Data](https://www.abs.gov.au/statistics/labour/employment-and-unemployment/labour-force-australia/latest-release)].\n  5. Google closing stock price on 23 May 2025 [[Data](https://finance.yahoo.com/quote/GOOG/)].\n\nFor each of these, give a **point forecast** and an **80% prediction interval**, and **explain in a couple of sentences** how each was obtained.\n\n* Prepare short justifications with your forecasts and forecast intervals explaining in no more than 50-70 words how these were obtained. Only a couple of sentences are required. There is no need to use any fancy models or sophisticated methods. \n* **Full marks will be awarded** if you submit the required information, and are able to meaningfully justify your results in a couple of sentences in each case. \n\n### Submission\n\nYour forecasts should be submitted in moodle by **9.30am, on Monday, March 10**.\n\n\n\n\n\n<br><br><hr><b>Due: 10 March 2025</b><br><a href=https://learning.monash.edu/mod/quiz/view.php?id=3877940 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF5231)</b>&nbsp;&nbsp;</font><br></a><br><br><hr><b>Due: 10 March 2025</b><br><a href=https://learning.monash.edu/mod/quiz/view.php?id=3877918 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF3231)</b>&nbsp;&nbsp;</font><br></a>\n\n\n\n\n\n\n\n#### Tips\n\n* The [Data] links give you possible data to start with, but you are free to use any data you like.\n* There is no need to use any fancy models or sophisticated methods. Simple is better for this assignment. The methods you use should be understandable to any high school student.\n\n## Forecasting competition\n\nOnce the true values in each case are available, we will come back to this exercise and see who did the best using the scoring method described in class. The student with the best score will be the winner of our forecasting competition (something really nice to have on your CV), and will also win a $100 Amazon gift voucher.\n\nNote: your assignment mark is not dependent at all on the score you obtain in the competition.\n\n\n### Scoring \n\\small\n\nLet $y=$ actual, $\\hat{y}=$ point forecast, $[\\hat{\\ell},\\hat{u}]=$ prediction interval\n\n#### Point forecasts:\n\n$$\\text{Absolute Error} = |y-\\hat{y}|$$\n\n\\vspace{-0.4cm}\n\n * Rank results for all students in class\n * Add ranks across all five items\n\n#### Prediction intervals:\n\n$$\n\\text{Interval Score} = (\\hat u - \\hat\\ell) + 10(\\hat\\ell - y)_+ + 10 (y-\\hat u)_+\n$$\n\n\\vspace{-0.5cm}\n\n* $u_+=max(u,0)$\n* Rank results for all students\n* Add ranks across all five items\n\n\n<!-- ### Submitted forecasts -->\n\n<!-- * [Q1](Q1.png); [Q1-zoom](Q1zoom.png). -->\n<!-- * [Q2](Q2.png); [Q2-zoom](Q2zoom.png). -->\n<!-- * [Q3](Q3.png); [Q3-zoom](Q3zoom.png). -->\n<!-- * [Q4](Q4.png); [Q4-zoom](Q4zoom.png). -->\n\n<!-- ### Leaderboard -->\n\n<!-- <iframe src=\"https://docs.google.com/spreadsheets/d/1_3RcdspMIL7TIaD7566bEbUEe8LHcg4UNQS1-ex-NZg/edit?usp=sharing\" width = \"110%\" height = 500></iframe> -->\n\n",
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       "rmarkdown/pagebreak.lua"

_freeze/assignments/A2/execute-results/html.json

@@ -2,7 +2,7 @@
   "hash": "01940f7fae546294603982d29e7e968e",
   "result": {
     "engine": "knitr",
-    "markdown": "---\ntitle: Individual Assignment 2 (7%)\n---\n\n\n\nUse the `IA2_template.Rmd` to get started. Leave the \"## Questions\" and the pagebreaks \"\\newpage\" as they are (do not remove these - these will help with marking the assignment). You are to submit both an \"IA2_NameSurname.Rmd\" file and a compiled `IA2_NameSurname.pdf` file for your assignment.\n\nFollow the assignment questions/instructions to complete some specific tasks. Add code where necessary (you can add more R chunks if and where you need to) and text to answer the questions where necessary. Keep within the suggested word restrictions in order to get full marks (marks will be deducted for grossly going over the word limit). This is to encourage you to be concise in your writing. \n\nYou will be using this data in future assignments as you will build on the analysis you perform in this assignment. Furthermore, in the final assignment you will need to submit an .Rmd file that you will develop for all the assignment tasks throughout the semester. Marks will be allocated for code that runs without errors and produces the correct output. Make sure that every time your code works without errors. If you need help with this, please ask during consultation times. Keeping detailed comments in your program is always good practice (see for example the programs we are using in the lectures). This will help you remember in week 12 why you did certain things in week 4. \n\n**Files for download**:\n\n* Download the template\n\n::: {.callout appearance=\"minimal\"}\n<i class=\"bi bi-download\"></i> [Download template](../assignment_data/IA2_template.Rmd.zip){download=\"IA2_template.Rmd.zip\"}\n:::\n\n* Download the data \n\n::: {.callout appearance=\"minimal\"}\n<i class=\"bi bi-download\"></i> [Download IA_data.csv](../assignment_data/IA_data.csv){download=\"IA_data.csv\"}\n:::\n\n\n\n\n\n<br><br><hr><b>Due: 7 April 2025</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=3444669 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF5231)</b>&nbsp;&nbsp;</font><br></a><br><br><hr><b>Due: 7 April 2025</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=3444670 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF3231)</b>&nbsp;&nbsp;</font><br></a>\n",
+    "markdown": "---\ntitle: Individual Assignment 2 (7%)\n---\n\n\n\nUse the `IA2_template.Rmd` to get started. Leave the \"## Questions\" and the pagebreaks \"\\newpage\" as they are (do not remove these - these will help with marking the assignment). You are to submit both an \"IA2_NameSurname.Rmd\" file and a compiled `IA2_NameSurname.pdf` file for your assignment.\n\nFollow the assignment questions/instructions to complete some specific tasks. Add code where necessary (you can add more R chunks if and where you need to) and text to answer the questions where necessary. Keep within the suggested word restrictions in order to get full marks (marks will be deducted for grossly going over the word limit). This is to encourage you to be concise in your writing. \n\nYou will be using this data in future assignments as you will build on the analysis you perform in this assignment. Furthermore, in the final assignment you will need to submit an .Rmd file that you will develop for all the assignment tasks throughout the semester. Marks will be allocated for code that runs without errors and produces the correct output. Make sure that every time your code works without errors. If you need help with this, please ask during consultation times. Keeping detailed comments in your program is always good practice (see for example the programs we are using in the lectures). This will help you remember in week 12 why you did certain things in week 4. \n\n**Files for download**:\n\n* Download the template\n\n::: {.callout appearance=\"minimal\"}\n<i class=\"bi bi-download\"></i> [Download template](../assignment_data/IA2_template.Rmd.zip){download=\"IA2_template.Rmd.zip\"}\n:::\n\n* Download the data \n\n::: {.callout appearance=\"minimal\"}\n<i class=\"bi bi-download\"></i> [Download IA_data.csv](../assignment_data/IA_data.csv){download=\"IA_data.csv\"}\n:::\n\n\n\n\n\n<br><br><hr><b>Due: 7 April 2025</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=3444670 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF5231)</b>&nbsp;&nbsp;</font><br></a><br><br><hr><b>Due: 7 April 2025</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=3444669 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF3231)</b>&nbsp;&nbsp;</font><br></a>\n",
     "supporting": [],
     "filters": [
       "rmarkdown/pagebreak.lua"

_freeze/assignments/A3/execute-results/html.json

@@ -1,7 +1,8 @@
 {
   "hash": "cef3d58e62b136835640c2868e9718ec",
   "result": {
-    "markdown": "---\ntitle: Individual Assignment 3 (10%)\n---\n\n\nThe data you are to forecast is the same series you used in IA2. \n\n**Files for download**:\n\n* Download the template\n\n::: {.callout appearance=\"minimal\"}\n<i class=\"bi bi-download\"></i> [Download template](../assignment_data/IA3_template.Rmd.zip){download=\"IA3_template.Rmd.zip\"}\n:::\n\n\nYou are to submit both an `IA3_NameSurname.Rmd` file and a compiled `IA3_NameSurname.pdf` file for your assignment.\n\n\n<br><br><hr><b>Due: 24 April 2024</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=1450550 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF3231)</b>&nbsp;&nbsp;</font><br></a><br><br><hr><b>Due: 24 April 2024</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=1450552 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF5231)</b>&nbsp;&nbsp;</font><br></a>\n",
+    "engine": "knitr",
+    "markdown": "---\ntitle: Individual Assignment 3 (10%)\n---\n\n\n\nThe data you are to forecast is the same series you used in IA2. \n\n**Files for download**:\n\n* Download the template\n\n::: {.callout appearance=\"minimal\"}\n<i class=\"bi bi-download\"></i> [Download template](../assignment_data/IA3_template.Rmd.zip){download=\"IA3_template.Rmd.zip\"}\n:::\n\n\nYou are to submit both an `IA3_NameSurname.Rmd` file and a compiled `IA3_NameSurname.pdf` file for your assignment.\n\n\n\n<br><br><hr><b>Due: 28 April 2025</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=3444674 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF5231)</b>&nbsp;&nbsp;</font><br></a><br><br><hr><b>Due: 28 April 2025</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=3444673 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF3231)</b>&nbsp;&nbsp;</font><br></a>\n",
     "supporting": [],
     "filters": [
       "rmarkdown/pagebreak.lua"

_freeze/assignments/A4/execute-results/html.json

@@ -1,7 +1,8 @@
 {
   "hash": "8f7c3aa5af4c1fa1c66d535efb588403",
   "result": {
-    "markdown": "---\ntitle: Individual Assignment 4 (18%)\n---\n\n\nThe data you are to forecast is the same series you used in IA2. \n\n**Files for download**:\n\n* Download the template\n\n::: {.callout appearance=\"minimal\"}\n<i class=\"bi bi-download\"></i> [Download template](../assignment_data/IA4_template.Rmd){download=\"IA4_template.Rmd\"}\n:::\n\n\n\n\nYou are to submit both an `IA4_NameSurname.Rmd` file and a compiled `IA4_NameSurname.pdf` file for your assignment.\n\n\n\n\n<br><br><hr><b>Due: 15 May 2024</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=1450556 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF3231)</b>&nbsp;&nbsp;</font><br></a><br><br><hr><b>Due: 15 May 2024</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=1450558 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF5231)</b>&nbsp;&nbsp;</font><br></a>\n",
+    "engine": "knitr",
+    "markdown": "---\ntitle: Individual Assignment 4 (18%)\n---\n\n\n\nThe data you are to forecast is the same series you used in IA2. \n\n**Files for download**:\n\n* Download the template\n\n::: {.callout appearance=\"minimal\"}\n<i class=\"bi bi-download\"></i> [Download template](../assignment_data/IA4_template.Rmd){download=\"IA4_template.Rmd\"}\n:::\n\n\n\n\nYou are to submit both an `IA4_NameSurname.Rmd` file and a compiled `IA4_NameSurname.pdf` file for your assignment.\n\n\n\n\n\n<br><br><hr><b>Due: 19 May 2025</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=3444678 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF5231)</b>&nbsp;&nbsp;</font><br></a><br><br><hr><b>Due: 19 May 2025</b><br><a href=https://learning.monash.edu/mod/assign/view.php?id=3444677 class = 'badge badge-large badge-blue'><font size='+2'>&nbsp;&nbsp;<b>Submit (ETF3231)</b>&nbsp;&nbsp;</font><br></a>\n",
     "supporting": [],
     "filters": [
       "rmarkdown/pagebreak.lua"