From 1ffd3dc506ed6154351faff1fa489713a0f79cd5 Mon Sep 17 00:00:00 2001 From: Rob J Hyndman Date: Thu, 30 Jan 2025 09:08:34 +1100 Subject: [PATCH] Fixed links on front page --- _freeze/index/execute-results/html.json | 4 ++-- index.qmd | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/_freeze/index/execute-results/html.json b/_freeze/index/execute-results/html.json index b449c8e..776e00f 100644 --- a/_freeze/index/execute-results/html.json +++ b/_freeze/index/execute-results/html.json @@ -1,8 +1,8 @@ { - "hash": "7a1649a81f0dc785ee0fa6cbbdaf1e05", + "hash": "4ef93beb249eec29ae0495ac28cf058b", "result": { "engine": "knitr", - "markdown": "---\ntitle: \"ETC3550/5550 Applied forecasting\"\n---\n\n\n\n## Teaching team\n### Lecturer/Chief Examiner\n\n\n:::: {.columns}\n\n::: {.column width=\"25%\"}\n\n![](https://robjhyndman.com/img/RJH_AAS_small.png){style=\"width: 80%;\"}\n:::\n\n::: {.column width=\"75%\"}\n\n[**Rob J Hyndman**](https://robjhyndman.com)\n\nEmail: [Rob.Hyndman@monash.edu](mailto:Rob.Hyndman@monash.edu)\n\n:::\n\n::::\n\n### Head Tutor\n\n:::: {.columns}\n\n::: {.column width=\"25%\"}\n\n![](/img/mitch.png){style=\"width: 80%;\"}\n:::\n\n::: {.column width=\"75%\"}\n\n[**Mitchell O'Hara-Wild**](https://mitchelloharawild.com)\n\nEmail: [Mitch.OHara-Wild@monash.edu](mailto:Mitch.OHara-Wild@monash.edu)\n\n:::\n\n::::\n\n### Tutors\n\n:::: {.columns}\n\n::: {.column .centeredcolumn width = \"33%\"}\n![](/img/maliny.png){style=\"width: 65%;\"}\n\nMaliny Poh\n\n:::\n\n::: {.column .centeredcolumn width = \"33%\"}\n![](/img/nuwani.png){style=\"width: 65%;\"}\n\nNuwani Palihawadana\n\n:::\n\n::: {.column .centeredcolumn width = \"33%\"}\n![](/img/sapphire.png){style=\"width: 65%;\"}\n\nXiefei (Sapphire) Li\n:::\n\n\n::::\n\n## Weekly schedule\n\n* [Pre-recorded videos](https://www.youtube.com/watch?v=uwKiT1o1TkI&list=PLyCNZ_xXGzpm7W9jLqbIyBAiSO5jDwJeE): approximately 1 hour per week [[Slides](https://github.com/robjhyndman/fpp3_slides)]\n* Tutorials: 1 hour per week\n* Online lecture: 12noon Mondays\n* Workshop: 1pm Tuesdays, [Lecture Theatre S3, 16 Rainforest Walk](https://maps.app.goo.gl/4AmDLWkY1yYZviFz8).\n\n\n\n|Week |Topic |Chapter |Assignments |Quizzes |\n|:------|:-----------------------------------|:--------------------------------|:-----------------------|:-------|\n|03 Mar |[Introduction to forecasting and R](./week1/index.html)|[1. Getting started](https://OTexts.com/fpp3/intro.html)| | |\n|10 Mar |[Time series graphics](./week2/index.html)|[2. Time series graphics](https://OTexts.com/fpp3/graphics.html)|[Forecasting Competition](assignments/competition.qmd)|[Week 2](https://learning.monash.edu/mod/quiz/view.php?id=3868353)|\n|17 Mar |[Time series decomposition](./week3/index.html)|[3. Time series decomposition](https://OTexts.com/fpp3/decomposition.html)| |[Week 3](https://learning.monash.edu/mod/quiz/view.php?id=3868355)|\n|24 Mar |[The forecaster's toolbox](./week4/index.html)|[5. The forecaster's toolbox](https://OTexts.com/fpp3/toolbox.html)|[Assignment 1](assignments/A1.qmd)|[Week 4](https://learning.monash.edu/mod/quiz/view.php?id=3868369)|\n|31 Mar |[Exponential smoothing](./week5/index.html)|[8. Exponential smoothing](https://OTexts.com/fpp3/expsmooth.html)| |[Week 5](https://learning.monash.edu/mod/quiz/view.php?id=3868370)|\n|07 Apr |[Exponential smoothing](./week6/index.html)|[8. Exponential smoothing](https://OTexts.com/fpp3/expsmooth.html)| |[Week 6](https://learning.monash.edu/mod/quiz/view.php?id=3868371)|\n|14 Apr |[ARIMA models](./week7/index.html) |[9. ARIMA models](https://OTexts.com/fpp3/arima.html)|[Assignment 2](assignments/A2.qmd)|[Week 7](https://learning.monash.edu/mod/quiz/view.php?id=3868372)|\n|21 Apr |Mid-semester break | | | |\n|28 Apr |[ARIMA models](./week8/index.html) |[9. ARIMA models](https://OTexts.com/fpp3/arima.html)| |[Week 8](https://learning.monash.edu/mod/quiz/view.php?id=3868373)|\n|05 May |[ARIMA models](./week9/index.html) |[9. ARIMA models](https://OTexts.com/fpp3/arima.html)| |[Week 9](https://learning.monash.edu/mod/quiz/view.php?id=3868374)|\n|12 May |[Multiple regression and forecasting](./week10/index.html)|[7. Time series regression models](https://OTexts.com/fpp3/regression.html)|[Assignment 3](assignments/A3.qmd)|[Week 10](https://learning.monash.edu/mod/quiz/view.php?id=3868375)|\n|19 May |[Dynamic regression](./week11/index.html)|[10. Dynamic regression models](https://OTexts.com/fpp3/dynamic.html)| |[Week 11](https://learning.monash.edu/mod/quiz/view.php?id=3868376)|\n|26 May |[Dynamic regression](./week12/index.html)|[10. Dynamic regression models](https://OTexts.com/fpp3/dynamic.html)|[Retail Project](assignments/Project.qmd)| |\n\n## Assessments\n\n* [Forecasting competition](assignments/competition.qmd): 2%\n* Weekly quizzes: 8%\n* [Assignment 1](assignments/A1.qmd): 6%\n* [Assignment 2](assignments/A1.qmd): 6%\n* [Assignment 3](assignments/A2.qmd): 6%\n* [Retail project](assignments/Project.qmd): 12%\n* Final exam: 60%\n\n## R package installation\n\nHere is the code to install the R packages we will be using in this unit.\n\n```r\ninstall.packages(c(\"tidyverse\",\"fpp3\", \"GGally\"), dependencies = TRUE)\n```\n", + "markdown": "---\ntitle: \"ETC3550/5550 Applied forecasting\"\n---\n\n\n\n## Teaching team\n### Lecturer/Chief Examiner\n\n\n:::: {.columns}\n\n::: {.column width=\"25%\"}\n\n![](https://robjhyndman.com/img/RJH_AAS_small.png){style=\"width: 80%;\"}\n:::\n\n::: {.column width=\"75%\"}\n\n[**Rob J Hyndman**](https://robjhyndman.com)\n\nEmail: [Rob.Hyndman@monash.edu](mailto:Rob.Hyndman@monash.edu)\n\n:::\n\n::::\n\n### Head Tutor\n\n:::: {.columns}\n\n::: {.column width=\"25%\"}\n\n![](/img/mitch.png){style=\"width: 80%;\"}\n:::\n\n::: {.column width=\"75%\"}\n\n[**Mitchell O'Hara-Wild**](https://mitchelloharawild.com)\n\nEmail: [Mitch.OHara-Wild@monash.edu](mailto:Mitch.OHara-Wild@monash.edu)\n\n:::\n\n::::\n\n### Tutors\n\n:::: {.columns}\n\n::: {.column .centeredcolumn width = \"33%\"}\n![](/img/maliny.png){style=\"width: 65%;\"}\n\nMaliny Poh\n\n:::\n\n::: {.column .centeredcolumn width = \"33%\"}\n![](/img/nuwani.png){style=\"width: 65%;\"}\n\nNuwani Palihawadana\n\n:::\n\n::: {.column .centeredcolumn width = \"33%\"}\n![](/img/sapphire.png){style=\"width: 65%;\"}\n\nXiefei (Sapphire) Li\n:::\n\n\n::::\n\n## Weekly schedule\n\n* [Pre-recorded videos](https://www.youtube.com/watch?v=uwKiT1o1TkI&list=PLyCNZ_xXGzpm7W9jLqbIyBAiSO5jDwJeE): approximately 1 hour per week [[Slides](https://github.com/robjhyndman/fpp3_slides)]\n* Tutorials: 1 hour per week\n* Online lecture: 12noon Mondays\n* Workshop: 1pm Tuesdays, [Lecture Theatre S3, 16 Rainforest Walk](https://maps.app.goo.gl/4AmDLWkY1yYZviFz8).\n\n\n\n|Week |Topic |Chapter |Assignments |Quizzes |\n|:------|:-----------------------------------|:--------------------------------|:-----------------------|:-------|\n|03 Mar |[Introduction to forecasting and R](./week1/index.html)|[1. Getting started](https://OTexts.com/fpp3/intro.html)| | |\n|10 Mar |[Time series graphics](./week2/index.html)|[2. Time series graphics](https://OTexts.com/fpp3/graphics.html)|[Forecasting Competition](assignments/competition.qmd)|[Week 2](https://learning.monash.edu/mod/quiz/view.php?id=3868353)|\n|17 Mar |[Time series decomposition](./week3/index.html)|[3. Time series decomposition](https://OTexts.com/fpp3/decomposition.html)| |[Week 3](https://learning.monash.edu/mod/quiz/view.php?id=3868355)|\n|24 Mar |[The forecaster's toolbox](./week4/index.html)|[5. The forecaster's toolbox](https://OTexts.com/fpp3/toolbox.html)|[Assignment 1](assignments/A1.qmd)|[Week 4](https://learning.monash.edu/mod/quiz/view.php?id=3868369)|\n|31 Mar |[Exponential smoothing](./week5/index.html)|[8. Exponential smoothing](https://OTexts.com/fpp3/expsmooth.html)| |[Week 5](https://learning.monash.edu/mod/quiz/view.php?id=3868370)|\n|07 Apr |[Exponential smoothing](./week6/index.html)|[8. Exponential smoothing](https://OTexts.com/fpp3/expsmooth.html)| |[Week 6](https://learning.monash.edu/mod/quiz/view.php?id=3868371)|\n|14 Apr |[ARIMA models](./week7/index.html) |[9. ARIMA models](https://OTexts.com/fpp3/arima.html)|[Assignment 2](assignments/A2.qmd)|[Week 7](https://learning.monash.edu/mod/quiz/view.php?id=3868372)|\n|21 Apr |Mid-semester break | | | |\n|28 Apr |[ARIMA models](./week8/index.html) |[9. ARIMA models](https://OTexts.com/fpp3/arima.html)| |[Week 8](https://learning.monash.edu/mod/quiz/view.php?id=3868373)|\n|05 May |[ARIMA models](./week9/index.html) |[9. ARIMA models](https://OTexts.com/fpp3/arima.html)| |[Week 9](https://learning.monash.edu/mod/quiz/view.php?id=3868374)|\n|12 May |[Multiple regression and forecasting](./week10/index.html)|[7. Time series regression models](https://OTexts.com/fpp3/regression.html)|[Assignment 3](assignments/A3.qmd)|[Week 10](https://learning.monash.edu/mod/quiz/view.php?id=3868375)|\n|19 May |[Dynamic regression](./week11/index.html)|[10. Dynamic regression models](https://OTexts.com/fpp3/dynamic.html)| |[Week 11](https://learning.monash.edu/mod/quiz/view.php?id=3868376)|\n|26 May |[Dynamic regression](./week12/index.html)|[10. Dynamic regression models](https://OTexts.com/fpp3/dynamic.html)|[Retail Project](assignments/Project.qmd)| |\n\n## Assessments\n\n* [Forecasting competition](assignments/competition.qmd): 2%\n* Weekly quizzes: 8%\n* [Assignment 1](assignments/A1.qmd): 6%\n* [Assignment 2](assignments/A2.qmd): 6%\n* [Assignment 3](assignments/A3.qmd): 6%\n* [Retail project](assignments/Project.qmd): 12%\n* Final exam: 60%\n\n## R package installation\n\nHere is the code to install the R packages we will be using in this unit.\n\n```r\ninstall.packages(c(\"tidyverse\",\"fpp3\", \"GGally\"), dependencies = TRUE)\n```\n", "supporting": [], "filters": [ "rmarkdown/pagebreak.lua" diff --git a/index.qmd b/index.qmd index 0a53e02..5e8df99 100644 --- a/index.qmd +++ b/index.qmd @@ -115,8 +115,8 @@ schedule |> * [Forecasting competition](assignments/competition.qmd): 2% * Weekly quizzes: 8% * [Assignment 1](assignments/A1.qmd): 6% -* [Assignment 2](assignments/A1.qmd): 6% -* [Assignment 3](assignments/A2.qmd): 6% +* [Assignment 2](assignments/A2.qmd): 6% +* [Assignment 3](assignments/A3.qmd): 6% * [Retail project](assignments/Project.qmd): 12% * Final exam: 60%