How to do sensitivity analysis with data table in Excel?
Let’s say you have a chair shop and sold chairs as below screenshot shown. Now, you want to analyze how the price and sales volume affect the profit of this shop simultaneously, so that you can adjust your sales strategy for better profit. Actually, the sensitivity analysis can solve your problem.
Do sensitivity analysis with data table in Excel
This method will apply the Data Table feature to do a sensitivity analysis in Excel. Please do as follows: Winrar for mac os x 10.6 free download.
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Falk reducers manual. 1. Finish the Profit & Loss Statement table as below screenshot shown:
(1) In Cell B11, Please type the formula =B4*B3;
(2) In Cell B12, please type the formula =B5*B3;
(3) In Cell B13, please type the formula =B11-B12;
(4) In Cell B14, please type the formula =B13-B6-B7.
(1) In Cell B11, Please type the formula =B4*B3;
(2) In Cell B12, please type the formula =B5*B3;
(3) In Cell B13, please type the formula =B11-B12;
(4) In Cell B14, please type the formula =B13-B6-B7.
2. Prepare the sensitivity analysis table as below screenshot shown:
(1) In Range F2:K2, please type the sales volumes from 500 to 1750;
(2) In Range E3:E8, please type the prices from 75 to 200;
(3) In the Cell E2, please type the formula =B14
(1) In Range F2:K2, please type the sales volumes from 500 to 1750;
(2) In Range E3:E8, please type the prices from 75 to 200;
(3) In the Cell E2, please type the formula =B14
Autocom 2013.3 keygen v1. 3. Select the Range E2:K8, and click Data > What-If Analysis > Data Table. See screenshot:
4. In the popping out Data Table dialog box, please (1) in the Row input cell box specify the cell with chairs sales volume (B3 in my case), (2) in the Column input cell box specify the cell with chair price (B4 in my case), and then (3) click the OK Disable_activation.cmd adobe. button. See screenshot:
5. Now the sensitivity analysis table is created as below screenshot shown.
You can easily get how the profit changes when both sales and price volume change. Mac ayres drive slow zip. For example, when you sold 750 chairs at price of $125.00, the profit changes to $-3750.00; while when you sold 1500 chairs at price of $100.00, the profit changes to $15000.00.
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- To post as a guest, your comment is unpublished.I built an Excel sensitivity analysis tool - https://causal.app/sensitivity. It figures out which variables in your model are the most important, and shows you what happens if you vary each variable one by one.
- To post as a guest, your comment is unpublished.Cell A11 should be Sales; Cell A12 should be Cost of Sales; Cell A13 should be Gross Profit while Cell A14 should be Operating Profit.
Celestine B. Etouwem.
Setup
1 First, if you haven't already, activate your Semantria account
During signup we sent you a confirmation email (check your Spam and Junk folders if it's not showing up)
Sentiment Analysis Addin For Excel On Mac Pdf
If you're already a confirmed Semantria user, you can proceed to the second step running an analysis.
2 Download Semantria for Excel
System requirements:
1) Microsoft Windows XP, Vista, 7, 8, 10
2) Microsoft Excel 2010, 2013 or 2016 (installed desktop version - trial or online-only versions will NOT work)
Mac Users: We have no native support for Mac, but you can run it through a Windows virtual machine setup
1) Microsoft Windows XP, Vista, 7, 8, 10
2) Microsoft Excel 2010, 2013 or 2016 (installed desktop version - trial or online-only versions will NOT work)
Mac Users: We have no native support for Mac, but you can run it through a Windows virtual machine setup
System recommendations:
1) 64bit Microsoft Excel
2) >4GB RAM
3) Dual core or better CPU
1) 64bit Microsoft Excel
2) >4GB RAM
3) Dual core or better CPU
Is my Excel 32 or 64 bit?
![Sentiment Analysis Addin For Excel On Mac Sentiment Analysis Addin For Excel On Mac](https://static.wixstatic.com/media/9d7f1e_364fec056b4f40c384a9dce1d6799a46~mv2.jpg/v1/fill/w_400,h_340,al_c,q_90/9d7f1e_364fec056b4f40c384a9dce1d6799a46~mv2.jpg)
Note: Check this as it is possible to have 32 bit Excel running on 64 bit Windows
Excel 2010 | File > Help > About Microsoft Excel |
Excel 2013 & 2016 | File > Account > About Excel |
3 Run the setup file on your computer
- Close Microsoft Excel if it is running
- Double-click on the installation file (Semantria.Excel.Setup.xXX.exe) and follow the on-screen instructions
- Complete the whole setup process
4 Enter your credentials in Excel
- Open Microsoft Excel
- A Semantria sign-in window will open
- Enter the username and password you provided during the signup process. You can also enter them after setup under [Settings > Sign-in] in the Lexalytics ribbon tab.
Running Your First Analysis
- In the Lexalytics tab in Microsoft Excel, click on Start to open the New Analysis wizard. (Troubleshooting)
- Import your text to analyze. If you want, use our sample data set below.Bellagio Reviews Dataset (.xlsx file)
- Categorize your data by ID, metadata, and the text to analyze. (If you don't see column names, click on 'First row has column headings')
- Select the rows to analyze.
- Name your project, select the appropriate language and configuration, in this case English, and click Next.
- Select the desired reports under Summary Reports and Detail Reports and they will generate. Clicking on the top half of the report buttons will auto-generate all of the reports in that category. Clicking on the bottom of the button will allow you to select individual reports. Then you may want to click 'Analytics panel' up next to the Start button in order to review the reports at full width.
Waiter and waitress training manual. You've completed your first analysis! For more help see our troubleshooting, step-by-step tutorials, customization tips, and fine-tuning
Reports
Summary Reports*
Except for the Query Co-occurrence report, all Summary reports will give you the top items of whatever the report type is. This report shows how many of those items were Positive, Neutral or Negative, as well as the total number of occurrences for that item. Summary reports also contain two Excel built charts based on the content of the report. Far cry 2 character differences. These visualizations are very basic. If you are interested in more visualization tools Semantria Storage and Visualization (SSV) might interest you.
The Query Co-occurrence report is the only unique Summary report. This report shows the how many documents hit on a cross section of the queries in the configuration.
- Sentiment Phrases
- Themes
- Entities
- Queries
- Concept Topics
- Autocategories
- Query Co-Occurence
Detail Reports*
Detail reports contain all the detailed output that Semantria generates when analyzing content. The Document Overview detail report will be generated at the same time as any other detail report, as detail reports have links in the ID column back to the Document Overview report.
- Document Overview
- Document ID:
- The ID of the document
- Status:
- The status returned from Semantria. “PROCESSED” means that the Document was processed correctly. Anything else will indicate a reason as to why the Document was not analyzed.
- Source Text:
- The text of the document that was analyzed
- Summary:
- A summary of the Document, the length of which depends on the summary length setting in the configuration that was used to analyze the content
- Detected Language:
- The language that Semantria believes the Document to be written in. NOTE this is NOT the language that the content was analyzed in. That is determined by the language of the configuration that was used to analyze the content.
- Detected Language Score:
- A score of how confident Semantria is that the Detected Language is correct
- Document Sentiment:
- The numerical sentiment score assigned to the Document
- Document Sentiment:
- The polarity of the sentiment score (Positive/Neutral/Negative)
- Metadata:
- If the user attached any Metadata to the analysis then those columns will be displayed after the Semantria output
- Words
- Word:
- A Word
- Type:
- The type of Word
- Number of Mentions:
- he number of times that Word occurs in all the documents
- Documents Count:
- The number of documents that Word occurs in
- Sentiment Phrases
- Document ID:
- The ID of the document (This is a link back to the Document Overview report)
- Highlighted Text:
- If the configuration used to analyze the content has Mentions enabled, then the highlighted phrase will appear in context here.
- Phrase:
- The sentiment phrase
- Phrase Sentiment:
- The numerical sentiment score assigned to the sentiment phrase
- Phrase Sentiment +/- :
- The polarity of the sentiment score (Positive/Neutral/Negative)
- Phrase Intensifiers:
- If the phrase is being intensified, then the intensifier will be listed here. Eg. 'very' or 'more' or 'super' etc.
- Phrase Negators:
- If the phrase is being negated, then the negator will appear here. Eg. 'not' or 'no'
- Metadata
- If the user attached any Metadata to the analysis then those columns will be displayed after the Semantria output
- Themes
- Document ID:
- The ID of the document (This is a link back to the Document Overview report)
- Highlighted Text:
- If the configuration used to analyze the content has Mentions enabled, then the highlighted theme will appear in context here.
- Theme:
- The detected theme. NOTE Themes are autodetected and not configurable
- Strength:
- Relevancy of the theme
- Theme Sentiment:
- The numerical sentiment score assigned to the theme
- Theme Sentiment +/- :
- The polarity of the sentiment score (Positive/Neutral/Negative)
- Theme Sentiment Evidence:
- Amount of sentiment evidence for this theme
- Theme Stemmed Form:
- Stemmed version of the theme
- Theme Normalized Name:
- Normalized version of theme
- Metadata:
- If the user attached any Metadata to the analysis then those columns will be displayed after the Semantria output
- Entity Themes
- Document ID
- The ID of the document (This is a link back to the Document Overview report)
- Highlighted Text
- If the configuration used to analyze the content has Mentions enabled, then the highlighted entity theme will appear in context here
- Entity
- The entity
- Entity Type
- The entity type
- Entity Theme
- The entity theme
- Entity Theme Sentiment
- The numerical sentiment score assigned to the entity theme
- Entity Theme Sentiment +/-
- The polarity of the sentiment score (Positive/Neutral/Negative)
- Entity Theme Sentiment Evidence
- Amount of sentiment evidence for this theme
- Metadata:
- If the user attached any Metadata to the analysis then those columns will be displayed after the Semantria output
- Entities
- Document ID:
- The ID of the document (This is a link back to the Document Overview report)
- Highlighted Text:
- If the configuration used to analyze the content has Mentions enabled, then the highlighted entity will appear in context here.
- Entity:
- The entity
- Entity Type:
- The entity type
- User-Defined Entity:
- A “yes” here indicates that the entity was defined by the user. A “no” indicates that the entity was autodetected.
- Entity Sentiment:
- The numerical sentiment score assigned to the Entity
- Entity Sentiment +/- :
- The polarity of the sentiment score (Positive/Neutral/Negative)
- Entity Sentiment Evidence:
- Amount of sentiment evidence for this entity
- Queries
- Document ID:
- The ID of the document (This is a link back to the Document Overview report)
- Highlighted Text:
- If the configuration used to analyze the content has Mentions enabled, then the highlighted query keyword will appear in context here.
- Query Category:
- The query that was hit on
- Query Category Sentiment:
- The numerical sentiment score assigned to the Query
- Query Category Sentiment +/- :
- The polarity of the sentiment score (Positive/Neutral/Negative)
- Query Category Relevancy:
- The number of query terms that hit in the document
- Metadata:
- If the user attached any Metadata to the analysis then those columns will be displayed after the Semantria output
- Concept Topics (Sometimes referred to as User Categories)
- Document ID:
- The ID of the document (This is a link back to the Document Overview report)
- Source Text:
- The text of the document where the Concept Topic was found
- Concept Topic:
- The Concept Topic
- Concept Topic Sentiment:
- The numerical sentiment score assigned to the Concept Topic
- Concept Topic Sentiment +/- :
- The polarity of the sentiment score (Positive/Neutral/Negative)
- Concept Topic Strength:
- The level of confidence that Semantria has that this Concept Topic applies to the document
- Metadata:
- If the user attached any Metadata to the analysis then those columns will be displayed after the Semantria output
- Autocategories
- Document ID:
- The ID of the document (This is a link back to the Document Overview report)
- Source Text:
- The text of the document where the Autocategory was found
- Autocategory:
- The Autocategory
- Subcategory:
- If there is a Subcategory, it will appear here
- Autocategory Sentiment:
- The numerical sentiment score assigned to the Autocategory
- Autocategory Sentiment +/- :
- The polarity of the sentiment score (Positive/Neutral/Negative)
- Autocategory Strength:
- This is the relevance score for the Autocategory
- Intentions
- Document ID:
- The ID of the document (This is a link back to the Document Overview report)
- Source Text:
- The text of the document where the Intention was found
- Intention Type:
- The type of Intention
- Who:
- Who does the Intention belong to
- What:
- What does the intention refer to
- Evidence:
- Evidence of the intention
- Metadata:
- If the user attached any Metadata to the analysis then those columns will be displayed after the Semantria output
- Machine Learning Models: This report is only available to those that have machine learning models installed in their configurations. This is not a standard feature, if you are interested in learning more about machine models please contact us.
Sentiment Analysis Addin For Excel On Mac Pdf
Tuning Reports*
- Uncategorized Documents: This report lists the documents that did not hit on any queries, and as such can be used to tune queries.
- Possible Sentiment Phrases: This report lists bi- and trigrams that could possibly be sentiment phrases. Note that these are not actually sentiment phrases, but rather they fit the pattern that other sentiment phrases do, so they are listed here as possible sentiment phrases that a user could add to their configuration.
- Query Comparison: This report compares the number of query hits from two separate analyses. This is useful in comparing an older analysis to a new one where you have made query changes.
- Sentiment Phrases for Queries: This report details the sentiment phrases that give a query its sentiment. The columns in this report are a combination of certain columns from the detail reports for queries and sentiment phrases, refer to the detail report information above for any clarification.
Note that you can see multiple sentiment phrases for one query result in this report.
* available tabs depend on the licensed features
Troubleshooting
Getting your log file:
- Launch the Run application on Windows (Press the Windows button and “r” at the same time for a shortcut.)
- In that window enter “%appdata%SemantriaExcelAddIn” without the quotes.
- Click OK
- In the window that opens you should see a “semantria” file of the type “Text Document”. This is your log file and should be attached to any email regarding an issue with the Excel plugin.