Data Analysis with Excel

Data Analysis with Excel

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1. Data Management and Manipulation

Learn how to import, clean, and transform data with advanced Excel functions to prepare datasets for in-depth analysis. Master techniques to navigate complex data with lookup functions.

Lookup Functions

2. Basic Data Analysis

Delve into the core of Excel's analytical power by mastering conditional analyses, statistical functions, and PivotTables. This section teaches you how to extract meaningful insights from large datasets using a variety of analytical tools.

Conditional Functions

Statistical Functions

Challenge: Midterm Exam

3. Data Visualization and Automation

Gain the skills to create statistical charts to build interactive dashboards that communicate data visually. Learn to automate repetitive tasks and generate reports efficiently, enhancing productivity and data interaction.

Charting Techniques

Statistical Charting

4. Advanced Data Analytics Techniques

It covers correlation analysis to determine relationships between variables using Pearson’s correlation coefficient, linear regression to explore variable relationships, the addition of trendlines for pattern analysis in forecasting, and the use of t-tests and z-tests in hypothesis testing to evaluate statistical significance.

Correlation Analysis

Regression Analysis

Building Trendlines and Forecasting

Hypothesis Testing

Course Content

Data Analysis with Excel

Data Analysis with Excel

1. Data Management and Manipulation

Data Import Data Cleanup Data Merging Lookup Functions

2. Basic Data Analysis

Conditional Functions Statistical Functions Pivot Tables Challenge: Midterm Exam

3. Data Visualization and Automation

Charting Techniques Statistical Charting Macros

4. Advanced Data Analytics Techniques

Correlation Analysis Regression Analysis Building Trendlines and Forecasting Hypothesis Testing

Conditional Functions

Conditional functions like SUMIFS and COUNTIFS allow users to perform complex data analyses by setting specific criteria.

These functions are critical for data-driven decision making and can then be used as a part of more complex calculations.

Task

First, please download the dataset we'll be using in this section:

Now let's use these functions to gain some insights:

Determine the total number of Hair Shampoos sold.
Find out how many transactions involved purchasing more than one Toy.

Note

The data shown in the video may differ from the data in the task's dataset, so ensure that your answer is based on the data from the downloadable file, not the video.

1. How many Hair Shampoos were sold?

2. How many transactions included purchasing more than one Toy?

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 1

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