Data Analysis With Microsoft Excel Update 2007 With Full book Download in PDF By Kenneth N. Berk and Patrick Carey
Many readers learn to solve practical everyday business issues quickly and make professional looking reports which incorporate graphics and spreadsheets by mastering the power of Microsoft Excel. This is an excellent program to use for a wide variety of business related tasks. This will not only save you time but will also save on money in the long run. You do not have to buy expensive software programs to accomplish this task. It is as simple as using Microsoft Excel. This article is designed to introduce users to some of the functions that are available with Microsoft Excel.
Data analysis with Microsoft Excel can be divided into two main categories. One of these methods involves the extraction of useful information from a set of data. The other method is much more difficult and may take several days or even weeks before the data is completely analyzed. In order to perform data analysis with Microsoft Excel, you will need to open a new workbook in Excel. It is recommended that you create a new workbook rather than saving an existing workbook because Excel saves the state of your workbook, making it easier to analyze the data later.
Once you open a new workbook, you will be able to select a data source, which can be a range of charts, graphs, or pie charts. You can then begin to analyze the data by navigating to the Data Analysis Toolbox, which is located in the Data tab on the ribbon. From here you will be able to select several different types of data sources, such as Excel documents, databases, and web data. You can also drill down to just the section or column you want more detailed information on.
Another option for data analysis with Microsoft Excel is to select the column that contains the value you want to analyze. You can then drill down to just that spot or you can select to drill all the way down to the underlying Excel document or the range of cells in the range you chose. If you select the latter, Excel will automatically extract all the relevant information from the file and present it to you in the format you desire. By default, Excel presents the data in rows and columns, but you can easily customize how you want the information to look by changing the style sheet in the Data Analysis pane of the Excel toolbar. All the options you need are located right below the Data tab.
When you select different types of data sources, such as Excel files, you will be prompted to enter a name for each one. The name you give to each tool is what will come up in your report. You may want to select different names for your pivot tables, charts, or graphs so that you can have a unique look each time you look at your results. By default, Excel provides a default name for all the different panes of your charts. If you would like some other name, you can change the default name, or you can even select different fonts for the different panes.
It’s important to remember how you select data in Excel. If you select a range of cells, for example, you are actually creating a new worksheet. In order to make sure that all the cells are presented in the same way, you should make sure that the width of the cell is proportional to the number of rows or columns in the range. Excel provides several different widths, which you can select from for your data source.
If you choose a random width for your range, Excel will automatically select the largest width possible. However, if you include a varying number of columns, Excel might choose the width of the range that is closest to the average value of the data. This is referred to as the average column width in Excel and is the one used in reports like the Financial Accounting summary report. If you create a range from a fixed number of values, Excel uses the mathematical mean of all the data points within the range. This makes it easier to calculate averages and means.
For more detailed data analysis, such as those that investigate relationships between variables, you should consider using the correlated variables approach in Microsoft Excel. Correlated variables are those that are influenced by another variable, but not necessarily linearly. For instance, the age of the person driving a vehicle will affect the probability that a vehicle accident will occur, but the age of the vehicle is influenced by many other factors. The age of the driver will therefore not linearly relate to the probability of an accident, but there are still some cases where an increase in the age of a driver would reduce the likelihood of accidents. For data analysis with Microsoft Excel, the correlated variables approach allows you to select the appropriate correlation for your data set and then determine its statistical significance.