Question

Data Visualization questions;

1. Please discuss briefly (50 words) tow datincts applications where data visualization can be used.

2. In about 50 words each, please comment on three distinct aspects of data visualization about which you learned in this topic.

Linear Regression Questions;

in 50 words each, discuss three distinct applications where linear regression could be used effectively. explain why each application is a good candidate for profuctive use of linear regression tools.

Answer 1

1. Data visualization is used in many disciplines and impacts how we see the world daily. It’s increasingly important to be able to react and make decisions quickly in both business and public services. We compiled a few examples of how data visualization is commonly used below.

• e.g.SALES AND MARKETING

According to research by the media agency Magna, half of all global advertising dollars will be spent online by 2020. Because of this, marketers need to stay on top of how their web properties are creating revenue along with their sources of web traffic. Visualizations can be used to easily see how traffic has trended over time as a result of marketing efforts.

• e.g.FINANCE

Finance professionals need to track the performance of their investment choices to make decisions to buy or sell a given asset. Candlestick visualization charts show how the price has changed over time, and the finance professional can use it to spot trends. The top of each candlestick represents the highest price within a period of time and the bottom represents the lowest. In the example, the green candlesticks show when the price went up and the red shows when it went down. The visualization can communicate the change in price more easily than a grid of data points.

2.

• Who is the audience, and how will it read and interpret the information? ...
• What are viewers' expectations, and what type of information is most useful to them?
• What is the visualization's functional role, and how can viewers take action from it?

3.

1. Linear Regression is a very powerful statistical technique and can be used to generate insights on consumer behaviour, understanding business and factors influencing profitability. Linear regressions can be used in business to evaluate trends and make estimates or forecasts. For example, if a company’s sales have increased steadily every month for the past few years, by conducting a linear analysis on the sales data with monthly sales, the company could forecast sales in future months.
2. Linear regression can also be used to analyze the marketing effectiveness, pricing and promotions on sales of a product. For instance, if company XYZ, wants to know if the funds that they have invested in marketing a particular brand has given them substantial return on investment, they can use linear regression. The beauty of linear regression is that it enables us to capture the isolated impacts of each of the marketing campaigns along with controlling the factors that could influence the sales. In real life scenarios there are multiple advertising campaigns that run during the same time period. Supposing two campaigns are run on TV and Radio in parallel, a linear regression can capture the isolated as well as the combined impact of running this ads together.
3. Linear Regression can be also used to assess risk in financial services or insurance domain. For example, a car insurance company might conduct a linear regression to come up with a suggested premium table using predicted claims to Insured Declared Value ratio. The risk can be assessed based on the attributes of the car, driver information or demographics. The results of such an analysis might guide important business decisions.