How to Analyse Data

Why is data analysis considered an essential skill in various roles and departments?

It's required for advanced degrees in statistics.

It helps inform decision making.

It's a hobby for "numbers people."

What is one key preparatory step before analyzing data?

Creating industry benchmarks.

Setting clear objectives and goals.

Using predictive analysis tools.

What is the primary purpose of cleaning data before analysis?

To create data visualizations.

To remove all data from the dataset.

To ensure accurate and usable insights.

Which tool is best suited for analyzing large data sets to spot trends and patterns?

Excel

Business Intelligence (BI) tools

Predictive analysis tools

What does "false causality" refer to in data analysis?

A statistical technique for analyzing unstructured data.

Correlation between two variables indicating a cause-and-effect relationship.

Incorrectly assuming causation based on correlation.

Why is it important to look for data that goes against your expectations?

To confirm your existing beliefs.

To cherry-pick findings that support your assumptions.

To avoid confirmation bias and ensure unbiased analysis.

What tool is used to visually represent data findings in charts and graphs?

Google Data Studio

Text analysis tools

Data cleaning tools

What should you do with the insights gained from data analysis?

Keep them for personal reference.

Use them to set targets and KPIs.

Share them only with upper management.

What is the ultimate purpose of data analysis?

To collect as much data as possible.

To create detailed data visualizations.

To make informed decisions based on insights.

Which type of data is challenging to analyze using traditional spreadsheets alone?

Qualitative data

Numerical data

Structured data

What can you use sentiment analysis for?

Analyzing numerical trends.

Detecting patterns in historical data.

Gauging positive or negative emotions in text data.

What's the importance of comparing current data against historical trends?

It's not important; current data is sufficient.

It provides context and helps identify changes over time.

It only applies to qualitative data analysis.

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