У нас вы можете посмотреть бесплатно Scatter Plots and Lines of Best Fit | Integrated Math 1 (2026 Update) или скачать в максимальном доступном качестве, видео которое было загружено на ютуб. Для загрузки выберите вариант из формы ниже:
Если кнопки скачивания не
загрузились
НАЖМИТЕ ЗДЕСЬ или обновите страницу
Если возникают проблемы со скачиванием видео, пожалуйста напишите в поддержку по адресу внизу
страницы.
Спасибо за использование сервиса ClipSaver.ru
In this lesson (3.5 Scatter Plots and Lines of Best Fit) we learn how to read and use scatter plots and how to draw a line of best fit (trend line). We start by defining what a scatterplot is (plotting raw data points) and how to describe the association in the data: positive correlation, negative correlation, or no correlation. Next, we talk about why correlation matters: if the pattern looks roughly linear, we can draw a trend line and write an equation to model the relationship. Once we have an equation, we can make predictions for values that are not in the original data set. You’ll see multiple examples where we: sketch a reasonable trend line (answers may vary), choose two clear points on the trend line, find slope (rise over run or slope formula), write an equation (point-slope form, then convert to slope-intercept form), interpret what slope and y-intercept mean in context, and use the model to predict an unknown value. 🔗 Visit www.clopensets.com for full class videos, guided notes, and printable worksheets that go along with this lesson. 🔗 ClopenSets shop: https://www.etsy.com/shop/Clopensets #education #maths #math #highschoolmath #highschool Chapters 00:00 What is a scatterplot? 00:20 Types of association: positive, negative, none 01:42 What correlation means + why trend lines help 02:54 Writing an equation from a trend line (overview) 02:59 Example 1: Hybrid cars sold (trend line + equation) 04:02 Choosing two points on the trend line 04:48 Slope calculation (slope formula) 05:22 Write equation and convert to y = mx + b 06:01 Interpret slope and y-intercept in context 06:38 Example 2: Temperature after sunset (trend line + equation) 07:08 Slope using rise over run 07:25 Write equation and simplify to y = mx + b 08:04 Interpret slope and y-intercept (cooling rate) 08:17 Example 3: Internet speed vs download time (scatterplot, trend line, model) 09:13 Choose two points + find slope 09:33 Write equation of trend line and simplify 10:37 Use the model to predict time when speed is 75