From a6871559279a368e03e5468f279829950ce89bd4 Mon Sep 17 00:00:00 2001 From: Vidushi Gupta <55969597+Vidushi-Gupta@users.noreply.github.com> Date: Thu, 8 Jun 2023 15:18:38 +0530 Subject: [PATCH] Moved hyperlink from heading to text --- 7-TimeSeries/1-Introduction/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/7-TimeSeries/1-Introduction/README.md b/7-TimeSeries/1-Introduction/README.md index 66af0a20..742b89c8 100644 --- a/7-TimeSeries/1-Introduction/README.md +++ b/7-TimeSeries/1-Introduction/README.md @@ -71,9 +71,9 @@ In the next lesson, you will build an ARIMA model using [Univariate Time Series] ✅ Identify the variable that changes over time in this dataset -## Time Series [data characteristics](https://online.stat.psu.edu/stat510/lesson/1/1.1) to consider +## Time Series data characteristics to consider -When looking at time series data, you might notice that it has certain characteristics that you need to take into account and mitigate to better understand its patterns. If you consider time series data as potentially providing a 'signal' that you want to analyze, these characteristics can be thought of as 'noise'. You often will need to reduce this 'noise' by offsetting some of these characteristics using some statistical techniques. +When looking at time series data, you might notice that it has [certain characteristics](https://online.stat.psu.edu/stat510/lesson/1/1.1) that you need to take into account and mitigate to better understand its patterns. If you consider time series data as potentially providing a 'signal' that you want to analyze, these characteristics can be thought of as 'noise'. You often will need to reduce this 'noise' by offsetting some of these characteristics using some statistical techniques. Here are some concepts you should know to be able to work with time series: