PMRTTCIPATTON

ACTTVTY

$1\mathrm{.}1\mathrm{.}3$: Descriptive, predictive, and prescriptive analytics.

Match each type of data analytics with the correct goal.

If unable to drag and drop, refresh the page.

$$

$$

$$

$q,$

$$ Given existing data, strives to summarize the data, perhaps to gain insight.

$$ Given data and a model, strives to determine future values.

$$ Strives to make decisions or recommendations based on data.

Feedback?

Types of data

Variables

Data is typically represented using variables. A variable is an item that can have different $($varying$")$ values. Ex: A persons age is a varace and can have the value $10\mathrm{.}33\mathrm{.}99$ or other values Variables are often considered as being of two possible types:

A quantitative variable can take on a numeric value $($quantitative data that can be measured and ordered. Ex A persons age the outside temperature and a meals price are quantitative variables. Example numeric values are an age of $33$ or $99$ years a temperature of $40$ or $45$ degrees and a price of $12$ or $15$ dotiars

A categorical variable can take on the va ue $($usually a labe$)$ of one of severa categores. Ex A persons gender seascons anc ds compan es are categorica variables Gendercan be male or temale seasons can be tal, winter spring or summer and Us $$t:rethan quartites