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## Feature Scaling meaning and methods with example in Excel

When you want to do some mathematical operation on two variables (in Excel on to column of data), then you need to note if those two variables are in the same scale or note, if not the end result may not show you a correct value. For example, in may machine learning algorithms, or in multi criteria decision making problems, or when you want to indicate the importance of some factors in quality management systems, you need to take average from some variables, but the average value will be more near to the variable with more data range scales.

In this video we show different feature scaling  methods such as Mini Max , Standardization , normalization, scale to unit length along with meaningful example.

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## Remove or edit empty or missed data in Excel

When your data set contains some cells that you don’t want them to be in your data set, then by using this tool you can choose to remove or replace those cells.

First you need to define which cells should be searched (for removing or replacing). For example, we can find empty cells, or cells that have just space character. Also you can define to find cells that contains some character or cells that exactly equal to something (searching is case sensitive)

then you need to select the desired operation to be done after finding cells. these operations are as follow:

1. Remove entire row: when Excel finds a cell with matched criteria, then it will remove the whole row related to that cell (good for removing all empty cells or missed data in data set)
2. Remove entire Column: when Excel finds a cell with matched criteria, then it will remove the whole column related to that cell ( good for removing columns or variables that are not desired)
3. Replacing the cell value with custom character:  you can enter any character that you want (number or words or other), then when Excel finds a cell with matched criteria, your entered character will be replaced with old character.
4. Replacing with average number: when your data set is numerical, you can choose to replace the missed cells with average number of previous and next (or above and below) cells .
5. Replacing with other cells value: Can choose to replacing the missed value of your data set be replaced by previous, next, above or below cells values.

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## Export multiple sheets from one Excel to one or multiple Excel files

sheets in our Excel file and export them into one or multiple new Excel file. For having multiple new Excel file you just simply need to choose a folder, then all selected sheets will be saved as new Excel file with their relative sheet name in destination folder.

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## Merge multiple Excel and sheets in one Excel

By using Extra tools add ins of Excel, we can simply select one or multiple Excel files (all Excel file in one folder) to insert their sheets in just one Excel file. If you select one Excel file, then you can choose which sheets to be inserted in your desired Excel file. If you want to merge multiple Excel files, then you need to move those Excel file in one folder. Then by choosing that folder from desired Excel by using Extra tools add ins, all of the worksheets in those Excel files will be copied in desired Excel

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## Install or remove add ins in Microsoft Excel

When there are some functionalities that can’t be done with regular tools of Excel (or any other software), then programmers try to write proper tools by their selves, these tools can be added to the original software and thus they are called add ins. There are lots of useful add ins that can be find in the different websites. In this video we show you how can we install or remove add ins in the Excel.

Extra tools add ins for Excel

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## Two-way analysis of variance – ANOVA – in Excel data analysis add in

The two way analysis of variance is a statistical method for determine if two independent variables has any effects on another variable. when we want to find out the relationship between these variables, we need to conduct an experiment in which, we have to change amounts in independent variables and then measuring the resulted amount in dependent variable. If we see meaningful changes in the average of resulted amounts, then we can conclude that the variable has effects. The method is called, analysis of variance, and in addition to that we have to test if the interaction of two independent variables have effects on the dependent variable or not. in this video we show how we can conduct the two-way ANOVA with replication (meaning that we have more than one sample for each variation in variables) in the Excel by using Data analysis add ins

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## One-way analysis of variance – ANOVA – in Excel data analysis add in

Analysis of variance is a statistical method for determine if a variable has any effects on another variable. when we want to find out the relationship between two variables, we need to conduct an experiment in which, we have to change amounts in one variable and then measuring the resulted amount in another one. If we see meaningful changes in the average of resulted amounts, then we can conclude that the first variable has effects on the second one. The method is called, analysis of variance, in this video we show how we can conduct the one-way ANOVA in the Excel by using Data analysis add ins

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## Test of hypothesis in Excel data analysis add in

When we have two sample data driven from one or two population and want to see if the mean of those two population (or the mean of one population between two different time) has been changed or not, we use statistical method called test of hypothesis for mean difference, which also known as AB test in some applications. Here we use data analysis add ins in the excel to generate this method in simple way.

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## Covariance and correlation in Excel data analysis add in

When we want to know if there is relationship between two or more variables, we need to calculate their covariance or correlation indexes. These to will show us how much two variables are related together. If these indexes have greater values (in correlation, near to 1), then showing us there is straight relation between variables. And if their values be huge negative number (in correlation, near to -1) then it showing the inverse relation between variables. However, if value of these indexes be near to 0, then it suggesting no relation between variables.