Microsoft Excel is one of the most popular applications for data analysis. Equipped with built-in pivot tables, they are without a doubt the most sought-after analytic tool available. It is an all-in-one data management software that allows you to easily import, explore, clean, analyze, and visualize your data. In this article, we will discuss the various methods of data analysis in Excel.
We will look into the following topics, in this article
Sorting data is a very critical and vital part of Data Analysis. You can sort your Excel data by multiple columns or even a single column. The sorting is done in ascending or descending order as well.
Consider the following data:
Let’s sort the data on the basis of Units. To do that, follow these steps:
Result:
Note: To sort in descending order, click ZA.
You can also sort on multiple columns in your worksheet. Execute the following steps.
The sort dialog box will appear.
We use filtering when we want to get the data that will match the specific conditions.
You can now filter according to your needs.
COUNTIF is a very commonly used Excel function used for counting cells in a range that satisfy a single condition.
Syntax:
=COUNTIF (range, criteria)
Example:
Let’s get the count of items that are over 100.
The Excel SUMIF function returns the sum of cells that meet a single condition.
Syntax:
=SUMIF (range, criteria, [sum_range])
Example:
Let’s use the SUMIF function to calculate the cells based on numbers that meet the criteria.
Pivot tables are known for being the most purposeful and powerful feature in Excel. We use them in summarizing the data stored in a table. They organize and rearrange statistics (or "pivot") to bring crucial and valuable facts to attention. It helps take an extremely large data set and see the relevant data you need in a crisp, easy, and manageable way.
The sample data that we are going to use contains 41 records with 5 fields of information on the buyer information. This data is perfect to understand the pivot table.
To insert a pivot table in your sheet, follow the steps mentioned below:
A dialog box will appear. Excel will auto-select your dataset. It will also create a new worksheet for your pivot table.
To get the total items bought by each buyer, drag the following fields to the following areas.
What-If Analysis is the process of changing the values to try out different values (scenarios) for formulas. You can use several different sets of values in one or multiple formulas to explore all the different results.
Perfect for what-if analysis, a solver is a Microsoft Excel add-in program that is helpful on many levels. You can use this feature to find an optimal (maximum or minimum) value for a formula in one cell, which is known as the objective cell. This is subject to some constraints, or limits, on the values of other formula cells on a worksheet.
Solver works with a group of cells, called decision variables or simply variable cells, used in computing the formulas in the objective and constraint cells. Solver also adjusts the decision variable cells' values to work on the limits on constraint cells. This thereby helps in producing the desired result for the objective cell.
In this example, we will try to find the solution for a simple optimization problem.
Problem: Suppose you are the owner of a business and you want your income to be $3000.
Goal: Calculate the units to be sold and price per unit to achieve the target.
For example, we have created the following model:
Your data model will change according to the conditions.
Descriptive statistics are one of the fundamental ‘must know’ information of any data set. It gives you an idea on:
Suppose we have a score of a batsman of his last 10 matches. To generate the descriptive analysis, follow the steps mentioned below.
Your descriptive statistics is ready.
ANOVA ( Analysis of variance ) in Excel is a statistical method that is used to test the difference between two or more means.
Below you can find the scores of three batsmen for their last 8 matches.
To implement the single factor ANOVA, follow the steps.
Your single factor ANOVA is ready.
In Excel, we use regression analysis to estimate the relationships between two or more variables.
Consider the following data where we have several COVID cases and masks sold in a particular month.
The following argument window will open.
Select the Input Y Range as the number of masks sold and Input X Range as COVID cases. Check the residuals and click OK.
You will get the Summary Output.
The Multiple R is the Correlation Coefficient that measures the strength of a linear relationship between two variables.
R Square signifies the Coefficient of Determination, which is used as an indicator of the goodness of fit. With the help of R Square, you can track how many points fall on the regression line.
Standard Error is another goodness-of-fit measure that shows the precision of your regression analysis.
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With this, we come to the end of this article on data analysis in Excel. We have seen and worked out some examples of some of the powerful methods and features of Excel data analysis.
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Aryan is a tech enthusiast who likes to stay updated about trending technologies of today. He is passionate about all things technology, a keen researcher, and writes to inspire. Aside from technology, he is an active football player and a keen enthusiast of the game.
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