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## Which of the following is predictive analytics?

Predictive analytics refers to using **historical data, machine learning, and artificial intelligence to predict what will happen in the future**. … Analysts can use predictive analytics to foresee if a change will help them reduce risks, improve operations, and/or increase revenue.

## Which of the following is a function of predictive analytics?

The correct answer is option C (to unlock the value of business intelligence for strategy). The main goal of predictive analytics is **to make strategies that can unlock business intelligence using statistical models**.

## What are the applications of predictive modeling?

Predictive analytics makes use of **statistics, modelling, data mining, artificial intelligence, machine language** to work on the current set of data provided as instructions and predict the future events.

## What are examples of predictive analytics?

**Predictive analytics examples by industry**

- Predicting buying behavior in retail. …
- Detecting sickness in healthcare. …
- Curating content in entertainment. …
- Predicting maintenance in manufacturing. …
- Detecting fraud in cybersecurity. …
- Predicting employee growth in HR. …
- Predicting performance in sports. …
- Forecasting patterns in weather.

## How do you explain predictive analytics?

Predictive analytics is a branch of advanced analytics that **makes predictions about future outcomes** using historical data combined with statistical modeling, data mining techniques and machine learning. Companies employ predictive analytics to find patterns in this data to identify risks and opportunities.

## Is K means a predictive model?

K is an input to the algorithm for predictive analysis; it stands for the number of groupings that the algorithm must extract from a dataset, expressed algebraically as k. A K-means algorithm **divides a given dataset into k clusters**.

## How do you conduct a predictive analysis?

**How do I get started with predictive analytics tools?**

- Identify the business objective. Before you do anything else, clearly define the question you want predictive analytics to answer. …
- Determine the datasets. …
- Create processes for sharing and using insights. …
- Choose the right software solutions.

## What is predictive analysis in research?

Predictive analysis is **about predicting the future**: data mining information from data sets and analyzing it in order to find patterns and predict future events or trends. … Because predictive analysis is often used against big data, organizations purchase other software to help them extract and analyze the data.

## What are the four primary aspects of predictive analytics?

**Predictive Analytics: 4 Primary Aspects of Predictive Analytics**

- Data Sourcing. …
- Data Utility. …
- Deep Learning, Machine Learning, and Automation. …
- Objectives and Usage.

## What is a good predictive model?

When evaluating data, a good predictive model should tick all the above boxes. If you want predictive analytics to help your business in any way, the data should **be accurate, reliable, and predictable across multiple data sets**. … Lastly, they should be reproducible, even when the process is applied to similar data sets.