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Excel Data Analysis: Sort, Filter, PivotTable, Formulas (25 Examples): HCC Professional Day 2012
 
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Download workbook: http://people.highline.edu/mgirvin/ExcelIsFun.htm Learn the basics of Data Analysis at Highline Community College Professional Development Day 2012: Topics in Video: 1. What is Data Analysis? ( 00:53 min mark) 2. How Data Must Be Setup ( 02:53 min mark) Sort: 3. Sort with 1 criteria ( 04:35 min mark) 4. Sort with 2 criteria or more ( 06:27 min mark) 5. Sort by color ( 10:01 min mark) Filter: 6. Filter with 1 criteria ( 11:26 min mark) 7. Filter with 2 criteria or more ( 15:14 min mark) 8. Filter by color ( 16:28 min mark) 9. Filter Text, Numbers, Dates ( 16:50 min mark) 10. Filter by Partial Text ( 20:16 min mark) Pivot Tables: 11. What is a PivotTable? ( 21:05 min mark) 12. Easy 3 step method, Cross Tabulation ( 23:07 min mark) 13. Change the calculation ( 26:52 min mark) 14. More than one calculation ( 28:45 min mark) 15. Value Field Settings (32:36 min mark) 16. Grouping Numbers ( 33:24 min mark) 17. Filter in a Pivot Table ( 35:45 min mark) 18. Slicers ( 37:09 min mark) Charts: 19. Column Charts from Pivot Tables ( 38:37 min mark) Formulas: 20. SUMIFS ( 42:17 min mark) 21. Data Analysis Formula or PivotTables? ( 45:11 min mark) 22. COUNTIF ( 46:12 min mark) 23. Formula to Compare Two Lists: ISNA and MATCH functions ( 47:00 min mark) Getting Data Into Excel 24. Import from CSV file ( 51:21 min mark) 25. Import from Access ( 54:00 min mark) Highline Community College Professional Development Day 2012 Buy excelisfun products: https://teespring.com/stores/excelisfun-store
Views: 1584350 ExcelIsFun
Data Analysis in Excel Tutorial
 
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Data Analysis using Microsoft Excel using SUMIF , CHOOSE and DATE Functions
Views: 114462 TEKNISHA
Module 1: Data Analysis in Excel
 
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This video is part of the Analyzing and Visualizing Data with Excel course available on EdX. To sign up for the course, visit: http://aka.ms/edxexcelbi
Views: 430255 DAT206x
Microsoft Excel data analysis tool for statistics mean, median, hypothesis, regression
 
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This video covers a few topics using the data analysis tool. After this video you should be able to: a) Find and use data analysis on excel to calculate statistics b) Calculate the mean, median, mode, standard deviation, range and coefficient variation on a variable set of data in excel. c) Conduct a confidence interval in excel. d) Complete a T-test in excel to help complete a hypothesis test. e) Conduct a linear regression analysis output from excel and create a scatter diagram.
Views: 111002 Me ee
Business Analytics with Excel | Data Science Tutorial | Simplilearn
 
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Business Analytics with excel training has been designed to help initiate you to the world of analytics. For this we use the most commonly used analytics tool i.e. Microsoft Excel. The training will equip you with all the concepts and hard skills required to kick start your analytics career. If you already have some experience in the IT or any core industry, this course will quickly teach you how to understand data and take data driven decisions relative to your domain using Microsoft excel. Data Science Certification Training - R Programming: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Data-Excel-W3vrMSah3rc&utm_medium=SC&utm_source=youtube For a new-comer to the analytics field, this course provides the best required foundation. The training also delves into statistical concepts which are important to derive the best insights from available data and to present the same using executive level dashboards. Finally we introduce Power BI, which is the latest and the best tool provided by Microsoft for analytics and data visualization. What are the course objectives? This course will enable you to: 1. Gain a foundational understanding of business analytics 2. Install R, R-studio, and workspace setup. You will also learn about the various R packages 3. Master the R programming and understand how various statements are executed in R 4. Gain an in-depth understanding of data structure used in R and learn to import/export data in R 5. Define, understand and use the various apply functions and DPLYP functions 6. Understand and use the various graphics in R for data visualization 7. Gain a basic understanding of the various statistical concepts 8. Understand and use hypothesis testing method to drive business decisions 9. Understand and use linear, non-linear regression models, and classification techniques for data analysis 10. Learn and use the various association rules and Apriori algorithm 11. Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: IT professionals looking for a career switch into data science and analytics Software developers looking for a career switch into data science and analytics Professionals working in data and business analytics Graduates looking to build a career in analytics and data science Anyone with a genuine interest in the data science field Experienced professionals who would like to harness data science in their fields Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 39254 Simplilearn
How to Install the Data Analysis ToolPak in Microsoft Excel
 
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Illustrates how to Add-In the Data Analysis ToolPak in Excel. Excel statistics data analysis toolpak. Check out our brand-new Excel Statistics Text: https://www.amazon.com/dp/B076FNTZCV In the text we cover installing the Data Analysis ToolPak and much more. YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Views: 245972 Quantitative Specialists
Introduction to Pivot Tables, Charts, and Dashboards in Excel (Part 1)
 
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WATCH PART 2: https://www.youtube.com/watch?v=g530cnFfk8Y Download file used in the video: http://www.excelcampus.com/pivot-table-checklist-yt In this video series you will learn how to create an interactive dashboard using Pivot Tables and Pivot Charts. Works with Excel 2003, 2007, 2010, 2013 for Windows & Excel 2011 for Mac Don't worry if you have never created a Pivot Table before, I cover the basics of formatting your source data and creating your first Pivot Table as well. You will also get to see an add-in I developed named PivotPal that makes it easier to work with some aspects of Pivot Tables. Download the files to follow along at the following link. http://www.excelcampus.com/pivot-table-checklist-yt I have another video that shows how to reformat the pivot chart in Excel 2010. In the video above I'm using Excel 2013 and the menus are different from Excel 2007/2010. Here is the link to that video. http://www.youtube.com/watch?v=Jt_QqG-vRRw Get PivotPal: http://www.excelcampus.com/pivotpal Free webinar on The 5 Secrets to Understanding Pivot Tables: https://www.excelcampus.com/pivot-webinar-yt Subscribe to my free newsletter: http://www.excelcampus.com/newsletter
Views: 7212606 Excel Campus - Jon
Excel 2013 Statistical Analysis #01: Using Excel Efficiently For Statistical Analysis (100 Examples)
 
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Download File: https://people.highline.edu/mgirvin/AllClasses/210Excel2013/Ch00/Excel2013StatisticsChapter00.xlsx All Excel Files for All Video files: http://people.highline.edu/mgirvin/excelisfun.htm. Intro To Excel: Store Raw Data, Data Types, Data Analysis, Formulas, PivotTables, Charts, Keyboards, Number Formatting, Data Analysis & More: (00:08) Introduction to class (00:49) Cells, Worksheets, Workbooks, File Names (02:54) Navigating Worksheets & Workbook (03:58) Navigation Keys (04:15) Keyboard move Active Sheet (05:40) Ribbon Tabs (06:25) Add buttons to Quick Access Tool Bar (07:40) What Excel does: Store Raw Data, Make Calculations, Data Analysis & Charting (08:55) Introduction to Data Analysis (10:37) Data Types in Excel: Text, Numbers, Boolean, Errors, Empty Cells (11:16) Keyboard Enter puts content in cell and move selected cell down (13:00) Data Type DEFAULT Alignments (13:11) First Formula. Entering Cell References in formulas (13:35) Keyboard Ctrl + Enter puts content in cell & keep cell selected (14:45) Why we don’t override DEFAULT Alignments (15:05) Keyboard Ctrl + Z is Undo (17:05) Proper Data Sets & Raw Data (24:21) How To Enter Data & Data Labels (24:21) Stylistic Formatting (26:35) AVERAGE Function (27:31) Format Formulas Differently than Raw Data (28:30) Keyboard Ctrl + C is Copy. Keyboard Ctrl + V is Paste (29:59) Use Eraser remove Formatting Only (29:19) Keyboard Ctrl + B adds Bold (29:57) Excel’s Golden Rule (31:43) Keyboard F2 puts cell in Edit Mode (32:01) Violating Excel’s Golden Rule (34:12) Arrow Keys to put cell references in formulas (35:40) Full Discussion about Formulas & Formulas Elements (37:22) SUM function Keyboard is Alt + = (38:22) Aggregate functions (38:50) Why we use ranges in functions (40:56) COUNT & COUNTA functions (42:47) Edit Formula & change cell references (44:18) Absolute & Relative Cell References (45:52) Use Delete Key, Not Right-click Delete (46:40) Fill Handle & Angry Rabbit to copy formula (47:41) Keyboard F4 Locks Cell Reference (make Absolute) (49:45) Keyboard Tab puts content in Cell and move selected Cell to right (50:55) Order of Operation error (52:17) Range Finder to find formula errors (52:34) Lock Cell Reference after you put cell in Edit Mode (53:58) Quickly copy an edited formula down a column (53:07) F2 key in last cell to find formula errors (54:15) Fix incorrect range in function (54:55) SQRT function & Fractional Exponents (57:20) STDEV.P function (58:10) Navigate Large Data Sets (58:48) Keyboard Ctrl + Arrow jumps to bottom of data set (59:42) Keyboard Ctrl + Shift + Arrow selects to bottom of data set (Current Range) (01:01:41) Keyboard Shift + Enter puts content in Cell and move selected Cell up (01:02:55) Counting with conditions or criteria: COUNTIFS function (01:03:43) Keyboard Ctrl + Backspace jumps back to Active Cell (01:05:31) Counting between an upper & lower limit with COUNTIFS (01:07:36) COUNTIFS copied down column (01:10:08) Joining Comparative Operator with Cell Reference in formula (01:12:50) Data Analysis features in Excel (01:13:44) Sorting (01:16:59) Filtering (01:20:39) Introduction to PivotTables (01:23:39) Create PivotTable dialog box (01:24:33) Dragging & dropping Fields to create PivotTable (01:25:31) Dragging Field to Row area creates a Unique List (01:26:17) Outline/Tabular Layout (01:27:00) Value Field Settings dialog to change: Number Formatting, Function, Name (01:28:12) 2nd & 3rd PivotTable examples (01:31:23) What is a Cross Tabulated Report? (01:33:04) Create Cross Tabulated Report w PivotTable (01:35:05) Show PivotTable Field List (01:36:48) How to Pivot the Report (01:37:50) Summarize Survey Data with PivotTable. (01:38:34) Keyboard Alt, N, V opens PivotTable dialog box (01:41:38) PivotTable with 3 calculations: COUNT, MAX & MIN (01:43:25) Count & Count Number calculations in a PivotTable (01:45:30) Excel 2013 Charts to Visually Articulate Quantitative Data (01:47:00) #1 Rule for Charts: No Chart Junk! (01:47:30) Explain chart types: Column, Bar, Pie, Line and X-Y Scatter Chart (01:51:34) Create Column Chart using Recommended Chart feature (01:53:00) Remove Field Buttons from Pivot Chart (01:54:10) Chart Formatting Task Pane (01:54:45) Vary Fill Color by point (01:55:15) Format Axis with Numbers by Formatting Source Data in PivotTable (01:56:02) Add Data Labels to Chart (01:57:28) Copy Chart & Create Bar Chart (01:57:48) Change Chart Type (01:58:15) Change Gap Width. (01:59:17) Create Pie Chart (01:59:23) Do NOT use 3-D Pie (01:59:42) Add % Data Labels to Pie Chart (02:00:25) Create Line Chart From PivotTable (02:01:20) Link Chart Tile to Cell (02:02:20) Move a Chart (02:02:33) Create an X-Y Scatter Chart (02:03:35) Add Axis Labels (02:05:27) Number Formatting to help save time (02:07:24) Number Formatting is a Façade (02:10:27) General Number Format (02:10:52) Percentage Number Formatting (02:14:03) Don’t Multiply Relative Frequency by 100 (02:17:27) Formula for % Change & End Amount
Views: 431944 ExcelIsFun
Data analysis with Excel: Titanic dataset
 
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In this video, you will see how to do some basic data analysis with Microsoft Excel. You'll see how to use various functions and get an introduction to use pivot tables Data source: https://www.kaggle.com/c/titanic/data Please comment if you want such set of videos. Cheers!
Views: 4156 Windows Tech Channel
Excel 2010 Data Analysis
 
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Excel 2010 Data Analysis and Descriptive Statistics
Views: 185810 jjmcgrory
Analyzing data using variance and standard deviation | Excel | lynda.com
 
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Analyze data using variance and standard deviation in Excel. Watch more Excel tutorials at http://www.lynda.com/Excel-tutorials/Analyzing-data-using-variance-standard-deviation/196583/375050-4.html?utm_campaign=XddpZQyaaqU&utm_medium=social&utm_source=youtube-earned This tutorial is from the Data-Analysis Fundamentals with Excel course presented by lynda.com author Curt Frye. The complete course provides an overview of the fundamentals, from performing common calculations to conducting Bayesian analysis with Excel. Connect with lynda.com: Facebook: http://bit.ly/fbldc Twitter: http://bit.ly/ldctw Google Plus: http://bit.ly/gplusldc LinkedIn: http://bit.ly/linkldc
Views: 19073 LinkedIn Learning
Be a data ninja: Best practices for analytics using Microsoft Excel - THR3017
 
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Do you work with large and quickly-changing data sets, multiple data sources, a wide range of report/spreadsheet customers, and do you need to respond with increasing agility? In this advanced session our Excel PMs go deep and share their best practices and tricks. See some of the coolest formulas, visualization hacks, and other cool ways to manipulate data in Excel.​
Views: 1246 Microsoft Ignite
Data Analysis in Excel 2016 [WEBINAR]
 
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Data analysis is one of the most common tasks performed in Excel. Whether for reviewing your personal accounts or presenting findings to your business, it is an essential skill for modern knowledge workers. In recent years, some of the major changes in Excel have been designed to extend its data analysis capabilities. As well as improvements to PivotTables, including the introduction of the Power Pivot Add-in, several new data visualisation features have been added as has Power Query. In addition, a few months ago a free, standalone Business Intelligence program was released: Power BI. This webinar will show you the key tools and functions to use when conducting data analysis in Excel 2016. By the end of the webinar you'll be able to handle data sets - from the very small to the very large - and present your findings using the most appropriate charts. We will look at Excel's main data analysis features: - PivotTables - Power Pivot - Visualisation features including Power Map - Recent additions and developments https://filtered.com/
Views: 31145 Filtered
Business Data Analysis with Excel
 
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Lecture Starts at: 8:25 Business data presents a challenge for the data analyst. Business data is often aggregated, recorded over time, and tends to exhibit autocorrelation. Additionally, and most problematically, the amount of business data is usually quite limited. These characteristics lead to a situation where many of the tools in the analyst's tool belt (e.g., regression) aren't ideal for the task. Despite these challenges, proper analysis of business data represents a fundamental skill required of Business/Data Analysts, Product/Program Managers, and Data Scientists. At this meetup presenter Dave Langer will show how to get started analyzing business data in a robust way using Excel – no programming or statistics required! Dave will cover the following during the presentation: • The types of business data and why business data is a unique analytical challenge. • Requirements for robust business data analysis. • Using histograms, running records, and process behavior charts to analyze business data. • The rules of trend analysis. • How to properly compare business data across time, organizations, geographies, etc.Where you can learn more about the tools and techniques. *Excel spreadsheets can be found here: https://code.datasciencedojo.com/datasciencedojo/tutorials/tree/master/Business%20Data%20Analysis%20with%20Excel **Find out more about David here: https://www.meetup.com/data-science-dojo/events/236198327/ -- Learn more about Data Science Dojo here: https://hubs.ly/H0hz7sf0 Watch the latest video tutorials here: https://hubs.ly/H0hz8rL0 See what our past attendees are saying here: https://hubs.ly/H0hz7ts0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 51542 Data Science Dojo
Data Analysis with Python for Excel Users
 
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A common task for scientists and engineers is to analyze data from an external source. By importing the data into Python, data analysis such as statistics, trending, or calculations can be made to synthesize the information into relevant and actionable information. See http://apmonitor.com/che263/index.php/Main/PythonDataAnalysis
Views: 185110 APMonitor.com
Excel Filter Basics (for quick data analysis)
 
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Find out how to filter your data in Excel. In this filter basics tutorial you'll learn the following: 1. The shortcut key to turn filter on and off in Excel 2. How to do approximate matches (filter for words that contain a specific word) 3. How to filter multiple columns 4. How to filter for "or" conditions 5. How to copy a filtered range to another sheet 6. How to use formulas (such as subtotal) to sum a filtered range 7. How to filter for values between 2 dates 8. How to filter based on color 9. How to turn your data set into an Excel table (shortcut key) 10. How to add totals to your Excel table 🡻 Download the workbook here 🡻 http://www.xelplus.com/excel-filter-basic-to-advanced/ ★★ Links to related videos: ★★ Check out my Excel Basics Playlist here: https://www.youtube.com/playlist?list=PLmHVyfmcRKyx1KSoobwukzf1Nf-Y97Rw0 ★ My Online Excel Courses ★ Courses ► https://courses.xelplus.com/ ✉ Subscribe & get my TOP 10 Excel formulas e-book for free https://www.xelplus.com/free-ebook/ EXCEL RESOURCES I Recommend: https://www.xelplus.com/resources/ Get Office 365: https://microsoft.msafflnk.net/15OEg Microsoft Surface: https://microsoft.msafflnk.net/c/1327040/451518/7593 GEAR Camera: https://amzn.to/2FLiFho Screen recorder: http://techsmith.pxf.io/c/1252781/347799/5161 Microphone: https://amzn.to/2DVKstA Lights: http://amzn.to/2eJKg1U Note: This description contains affiliate links, which means at no additional cost to you, we will receive a small commission if you make a purchase using the links. This helps support the channel and allows us to continue to make videos like this. Thank you for your support! #MsExcel
Views: 28387 Leila Gharani
Excel 2016 Data Analysis ToolPak Histograms and Percent Polygons
 
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This how-to walks you through the process of using the Data Analysis ToolPak to visualize data distributions. This process is different from the pivot table method and provides results that are more easily compared. I detail the process of generating a histogram for each outcome and a plot of several percent polygons to compare several distributions.
Views: 7537 DrRyanPhelps
How to Use Excel for Data Analytics | Excel Tutorial for Data Analytics | Data Analytics Tutorial
 
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How to Use Excel for Data Analytics | Excel Tutorial for Data Analytics | Data Analytics Tutorial https://acadgild.com/big-data/data-analytics-training-certification?aff_id=6003&source=youtube&account=zDchks6coak&campaign=youtube_channel&utm_source=youtube&utm_medium=excel-for-data-analytics1&utm_campaign=youtube_channel Hello and welcome to Excel tutorial for analytics powered by Acadgild. In this tutorial, you will be able to learn, how to use Excel for data analysis. Let’s look at the agenda of this analytics tutorial. • Exploring Excel 2013 Interface • Accessing Data • Saving Data to Different File Formats • Formatting Data in Cells • Formatting Data • Arranging Data • Arranging Data – Sort • Arranging Data – Filter • Arranging Data – Group • Converting Data to Insights Kindly go through the complete video and learn how to use Excel for data analysis and become a data analyst. Please like and share the video and kindly give your feedbacks and subscribe the channel for more tutorial videos. For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 4775 ACADGILD
Analyzing And Visualizing Data With Excel 2016
 
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In this workshop, get an introduction to the latest analysis and visualization capabilities in Excel 2016. See how to import data from different sources, create mash/ups between data sources, and prepare the data for analysis. After preparing the data, learn about how business calculations - from simple to more advanced - can be expressed using DAX, how the result can be visualized and shared.
Views: 34172 Microsoft Power BI
MS Excel - Statistical Functions
 
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MS Excel - Statistical Functions Watch More Videos at: https://www.tutorialspoint.com/videotutorials/index.htm Lecture By: Mr. Pavan Lalwani, Tutorials Point India Private Limited
Excel Magic Trick 1242: Transform Large Data Set to Final GDP Report: TTC, MATCH, Filter & Format
 
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Download File: http://people.highline.edu/mgirvin/ex... Learn how to Take Large Data Set with Country Economic Data for the years 1970 to 2013 and filter, delete and match just the data we want to create a smaller data set using Text To Columns, MATCH function, TRIM function, Filter, Formatting and Page Setup: 1. (00:08) Discuss our task of taking a lot of data, removing only what we want, and then formatting and doing page setup on final report 2. (01:06) Text To Columns to get county names for our report 3. (01:54) TRIM function to remove extra spaces 4. (02:23) Copy Paste Special Values AND Transpose 5. (03:06) MATCH & ISNUMBER functions to create helper column to match countries we need in our final report 6. (04:07) Filter to get Counties and GDP numbers 7. (04:44) Delete Year Columns we do not need. 8. (05:02)Highlight Filtered Table to get Visible Cells Only and paste records to new sheet 9. (05:21) Delete non-adjacent columns in report that are not need in final report 10. (05:33) Display Numbers in Millions using Custom Number formatting: #,##0,, 11. (06:10) Display Years with an M to indicate numbers are shown in millions using Custom Number formatting: 0” M” 12. (06:43) Making sure that we have title that indicates the monetary unit: Constant 2005 US Dollars 13. (07:05) Apply Table Design Principles 14. (07:05) Add Border below Field Names 15. (07:17) Alternate shading for columns with white and light blue to help the visual ease of reading report 16. (08:25) Make sure that text is aligned left and numbers are aligned right 17. (08:39) Page Set Up so report prints correctly Mr Excel & excelisfun Trick 174: Clean & Transform GDP Data Set: Advanced Filter? Or Power Query? Excel Magic Trick 1243: Transform GDP Data Set: Power Query 2nd Method or Advanced Filter? Basic Excel Business Analytics Transforming Data
Views: 49058 ExcelIsFun
Highline Excel 2016 Class 03: Data Analysis Fundamentals: PivotTables, Power Query & Data Model
 
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Download Files: https://people.highline.edu/mgirvin/AllClasses/218_2016/218Excel2016.htm Buy excelisfun products: https://teespring.com/stores/excelisfun-store In this video learn about the fundamentals of Data Analysis and Business Intelligence in Excel 2016: Sort, Filter, PivotTables, Power Query, Power Pivot Data Model: 1. (00:05) Introduction 2. (01:39) Sort 3. (03:02) Sorting one column 4. (03:23) Sorting multiple columns 5. (09:06) Sorting Mixed Data 6. (10:50) Filter feature 7. (13:22) Filter Drop-down Arrows to see Unique List 8. (15:34) Filter Different Data Types 9. (18:30) Filter to Extract Records 10. (20:54) OR Logical Test (OR Criteria) Discussion 11. (22:52) AND Logical Test (AND Criteria) Discussion 12. (28:23) BETWEEN and NOT Criteria 13. (30:57) PivotTable. Discussion of Crosstabulated tables and PivotTables as “Calculations with Criteria”, both AND Criteria and OR Criteria. 14. (33:05) PivotTable Basics: 1) Drag and Drop Field Names to add criteria to PivotTable, 2) Cross Tabulated Table, 3) Layout Formatting, 4) Number Formatting 15. (37:41) Adding Slicers 16. (40:21) Creating a Custom Style for a PivotTable 17. (44:48) Name PivotTable 18. (46:12) Create PivotTable using “Summarize Values By”, which allows us to change the Aggregate Functions like: SUM, COUNT, AVERAGE. 19. (51:49) Group Dates by Month and Year 20. (54:50) Create PivotTable using “Show Values As” to calculate “% of Column Total”. 21. (56:09) Hide items in Slicer 22. (57:24) Connect Multiple Slicers to Multiple PivotTables. 23. (58:57) Sort in PivotTable. 24. (01:00:11) Create multiple PivotTables with a single click using “Show Report Filter Pages” 25. (01:03:10) Why we need Power Query and Power Pivot Data Model 26. (01:05:21) Introduction to Power Query (Get & Transform) 27. (01:07:04) Power Query Example 1: Clean and Transform Data Table, Create PivotTable Based on Power Query Update, 3) Add new data to table and Refresh to update Query and PivotTable 28. (01:18:25) Power Query to Unpivot a Crosstabulated Table into a Proper Data Set. 29. (01:24:54) Introduction to Power Pivot and the Data Model 30. (01:25:32) Power Query to import multiple Text File tables with over one million records combine them into a single Table. We will use the “From File, From Folder” option. 31. (01:33:20) Load the million records in Power Query into the Power Pivot Data Model. 32. (01:34:42) Add an Excel Table into the Power Pivot Data Model 33. (01:35:30) Update Power Query 34. (01:36:36) Build a relationship between tables in the Power Pivot Data Model. 35. (01:38:08) Build PivotTable from Millions of Records from Two Tables 36. (01:40:34) Add new Text File to Folder and Update PivotTable. 37. (01:41:22) Summary
Views: 266277 ExcelIsFun
SAP Analysis for Microsoft Office Excel
 
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SAP Business objects Business intelligence MS Office Excel based reporting. The source system is HANA Modeling Views. Connections and reporting options.
Views: 62058 Learn Today
Descriptive Statistics - Excel Data Analysis ToolPak
 
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Descriptive Statistics Generation - Excel Data Analysis ToolPak. Data set used can be downloaded at http://www.learnanalytics.in/blog/wp-content/uploads/2013/04/car_sales.xlsx
Views: 32977 Learn Analytics
Simple Linear regression analysis using Microsoft Excel's data analysis toolpak and ANOVA Concepts
 
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Knowledge Varsity (www.KnowledgeVarsity.com) is sharing this video with the audience.
Views: 136997 KnowledgeVarsity
Excel 2013 Statistical Analysis #8: Frequency Distributions, Histograms, Skew, Quantitative Variable
 
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Download files: http://people.highline.edu/mgirvin/excelisfun.htm Topics in this video: 1. (00:09) Overview of Frequency Distributions for Quantitative Variable 2. (02:02) Create Frequency Distribution with PivotTable for Grade Data where NUMBERS ARE DECIMALS (important distinction for grouping feature in a PivotTable) 3. (03:08) Grouping Feature in a PivotTable for creating Classes or Categories for a Decimal Quantitative Variable. Class that are created are 0-10, 10-20, 20-30, etc. Extensive Discussion about how to create classes or categories that are NOT Ambiguous. 4. (05:03) Upper Limit for Class/Category is Not Included when the numbers are Decimals. 5. (05:58) Aggregate Function for Number Values defaults to Count when you have Grouped Numbers in the Row area of the PivotTable. 6. (06:32) Double Click PivotTable to Extract Records that match the criteria from the Row area of the PivotTable 7. (09:16) Use Find and Replace feature to create non-ambiguous labels in a Grouped Decimal Number PivotTable. 8. (10:20) Create Histogram for Quantitative Variable (Grouped Numbers) for Grade Data. This Histogram has Frequencies at the top of each column and the gap width is zero. The colors for each column are different. 9. (13:13) Create Frequency Distribution with PivotTable for Grade Data where numbers are WHOLE NUMBERS (important distinction for grouping feature in a PivotTable) 10. (14:33) Methods for determining Number of Classes and Class Width for a Quantitative Variable 11. (18:19) When grouping Whole Numbers in a PivotTable the classes that are created are not ambiguous. We get classes like: 16-22, 23-29, 30-36. Etc. 12. (20:07) Create Histogram for Quantitative Variable (Grouped Numbers) for Age Data. This Histogram has Frequencies in the vertical axis and the gap width is zero. The colors for each column are the same. 13. (22:00) Discussion about Skew, Histogram shape and Histogram distribution of column heights. 14. (25:37) Relative Frequency and Percent Frequency Distribution built with a PivotTable based on Age Data that is shown as a Whole Number. 15. (27:48) Formulas 16. (27:44) Create Frequency Distribution with Formulas for Grade Data. 17. (30:03) Text Formulas for Category Labels 18. (30:40) COUNTIFS function with Comparative Operators Joined to Lower and Upper Limits from the Cells. 19. (33:17) Relative/Percent Frequency Formula. 20. (34:00) Create Histogram for Grade Data based on Frequency Distribution created with formulas. 21. (35:56) See that we can change the categories be more precise when we use formulas. 22. (38:20) Link Data Labels in Chart to cells in the spreadsheet 23. (39:16) See how formulas allow Frequency Distribution Formulas and Histogram Chart update automatically when raw data change. See different grade distributions with Histogram. 24. (40:45) Summary
Views: 165307 ExcelIsFun
Excel Data Analysis ToolPak - Building a Correlation Matrix
 
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We demonstrate installing Data Analysis ToolPak excel addin and how to build a Karl Pearson Correlation Matrix easily. The data set used can be downloaded from http://www.learnanalytics.in/blog/?p=150 . Please subscribe to our channel to receive updates and also join our Linkedin Group for latest training videos and articles @http://www.linkedin.com/groups/Learn-Analytics-step-time-4240061
Views: 121324 Learn Analytics
Simple Data Analysis for Teachers Using Excel
 
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Exploring some basic data analysis in excel
Views: 49865 Jon Jasinski
Excel Training | How To Create Beautiful Analytics Dashboard Report in Microsoft Excel
 
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About this Microsoft Office 365 Excel Training Video: How To Create Beautiful Web Analytics Dashboard Report in Microsoft Excel. For better visibility, watch in full screen mode (Full HD). Tool Used: MS Office 365 Excel Subscribe to Creative Venus: https://www.youtube.com/c/CreativeVenus/?sub_confirmation=1 Download Excel Template: https://drive.google.com/open?id=1oMsXsAOUWCu2cQMN9tdzORVsHdbKZEOE I hope you like this Microsoft Office 365 Excel Training Video. Please Like, share, comment and subscribe to watch more such videos. Follow Us on Google Plus: https://plus.google.com/u/0/109609798992670836043 Follow Us on Twitter: https://twitter.com/creative_venus Follow Us on Facebook: https://www.facebook.com/creativevenus4u/
Views: 139373 Creative Venus
How to Clean Up Raw Data in Excel
 
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Al Chen (https://twitter.com/bigal123) is an Excel aficionado. Watch as he shows you how to clean up raw data for processing in Excel. This is also a great resource for data visualization projects. Subscribe to Skillshare’s Youtube Channel: http://skl.sh/yt-subscribe Check out all of Skillshare’s classes: http://skl.sh/youtube Like Skillshare on Facebook: https://www.facebook.com/skillshare Follow Skillshare on Twitter: https://twitter.com/skillshare Follow Skillshare on Instagram: http://instagram.com/Skillshare
Views: 100510 Skillshare
Data Analysis In Excel 2013
 
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This is how to get to the Data Analysis menu in Excel 2013 to do a very simple t-test. This is meant for a BIO101 laboratory assignment.
Views: 94501 Nick Dowdy
Introduction to Data Analytics with R, Tableau & Excel | Data Analytics Career in 2019 & Beyond
 
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Introduction to Data Analytics with R, Tableau & Excel | Data Analytics Career in 2019 & Beyond https://acadgild.com/big-data/data-analytics-training-certification?aff_id=6003&source=youtube&account=UgnojgSKQLk&campaign=youtube_channel&utm_source=youtube&utm_medium=intro-DA-R-tableau-excel&utm_campaign=youtube_channel Did you know? by 2020, every human being will create over 1.5 megabytes of data per second on average. In 2025, the sum of digital data will add up to 180 zettabytes, which is over 1600 trillion gigabytes. Considering these numbers, it is an understatement to say that the data is only BIG. So, what is Big Data and how is it related to Data Analytics? Big data is a large volume of data that consists of both structured and unstructured data forms. helps organizations to draw meaningful insights from their data to learn and grow. Thus, it’s the data that matters and not it’s volume. Structured data is organized information that can be accessed with the help of simple search algorithms. While Unstructured data as the name suggests is less uniform and thus difficult to work with. The lack of structure makes compiling data at a time and energy-consuming task. The Relation Between Big Data and Analytics: The process of uncovering hidden patterns, unknown correlations, market trends, customer preferences and other useful information from both structured and unstructured data is called Data analytics. The Benefits of Using Data Analytics. • Analytics help organizations make informed decisions and choices. • It boosts the overall performance of the organization by refining the financial processes, increasing visibility, providing insights and granting control over managerial processes. • It detects fraud and flaws by keeping a close vigil. • It further Improves the IT economy by increasing agility and flexibility of systems. The above mentioned are just a few advantages, however, the list goes on. Despite the growing interest in data analytics, there is an acute shortage of professionals with good data analytical skills. Thus, only 0.5% of the data we produce is analysed. There is a serious shortage of skilled professionals. Thus, the ones who are called proficient data analysts must have certain skills. They must possess a varied skill-set like computer science, data mining and business management to provide from the data they are working on. Their computer science skills should include both programming skills and technical skills • Programming Skills: Python, R, and Java • Technical Skills: Knowledge of platforms like Hadoop, Hive, Spark, etc., Their data skills should include Warehousing Skills, Quantitative & Statistical Skills & Analytical & Interpretation Skills • Warehousing Skills: Data scientist must possess good analytical skills • Quantitative & Statistical Skills: As technology is a key aspect of big data analysis, quantitative and statistical skills are essential • Analytical & Interpretation Skills: knacks to analyses and interpret data The business skills are important to use the data effectively and to improve various aspects such as operations, finance, productivity, etc., These are the skills that make the data analytics professional an invaluable asset to the organization. The lack of skilled data professionals is an opportunity in turn for upcoming data scientists to make their mark in the field of data analytics. As the significance of data grows in the business world, the value of professionals working in analytics also increases. This is creating a variety of job roles amongst organizations and they are. Data Analyst, Analytics Consultant, Business Analyst, Analytics Manager, Data Architect, Metrics and Analytics Specialist, Analytics Associate these are only some of the job titles that data analytics professionals can acquire in business organizations. The list is presumably greater. The Chief Software Platforms are R, Tableau & Excel R is one of the robust statistical computing solutions. Tableau is the foremost business intelligence platform that offers eminent data visualization and exploration capabilities. Coming to Excel, it is used for managing, manipulating and presenting data. When combined, Tableau, R and Excel offer the most powerful and complete data analytics solutions. So, the demand for data analytics and its professionals is augmenting at a great pace. Organizations are interested in analysts to maximize their data potential, while professionals are interested in capitalizing on the analytical crunch in many parts of the world. #DataAnalytics, #Tableau, #R, #Excel, #career Please like share and subscribe the channel for more such video. For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 3917 ACADGILD
Data Analysis In Excel Max Min Mode Median Hindi
 
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Data Analysis in Excel Course- learn the basics of Data Analysis by understanding the Min formula, Max formula, Median Formula and Mode.sngl formulain Excel . The 4 formulas allow you to analysis data for basic traits like lowest value, highest value, the value in middle and the most commonly occurring value. At the end of the video there's a simple and effective chart tutorial also. To watch more videos and download the files visit http://www.myelesson.org To Buy a Excel Course DVD visit . https://www.instamojo.com/Devika/combo-pack-all-in-one-ms-excel-course-cd-in-/ 10 Most Used Formulas MS Excel https://www.youtube.com/watch?v=KyMj8HEBNAk Learn Basic Excel Skills For Beginners || Part 1 https://www.youtube.com/watch?v=3kNEv3s8TuA 10 Most Used Excel Formula https://www.youtube.com/watch?v=2t3FDi98GBk **Most Imporant Excel Formuls Tutorials** Learn Vlookup Formula For Beginners in Excel https://www.youtube.com/watch?v=vomClevScJQ 5 Excel Questions Asked in Job Interviews https://www.youtube.com/watch?v=7Iwx4AMdij8 Create Speedometer Chart In Excel https://www.youtube.com/watch?v=f6c93-fQlCs Learn the Basic of Excel for Beginners || Part 2 https://www.youtube.com/watch?v=qeMSV9T1PoI Create Pareto Chart In Excel https://www.youtube.com/watch?v=2UdajrDMjRE How to Create Dashboard in Excel https://www.youtube.com/watch?v=RM8T1eYBjQY Excel Interview Questions & Answers https://www.youtube.com/watch?v=Zjv1If63nGU
Views: 23686 My E-Lesson
10 Super Neat Ways to Clean Data in Excel
 
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Learn how to clean data in Excel using different ways and techniques. Data forms the backbone of any analysis that you do in Excel. And when it comes to data, there are tons of things that can go wrong – be it the structure, placement, formatting, extra spaces, and so on. Excel can be an amazing tool for data analysis. But we hardly get the data that can be used right away. And a bad data leads to bad analysis. In this video, I will show you 10 simple ways to clean data in Excel. The following topics are covered in this video: -- Get Rid of Extra Spaces -- Select and Treat All Blank Cells -- Convert Numbers Stored as Text into Numbers -- Remove Duplicates -- Highlight Errors -- Change Text to Lower/Upper/Proper Case -- Spell Check -- Delete all Formatting -- Use Find and Replace to Clean Data in Excel Read the full tutorial here: https://trumpexcel.com/clean-data-in-excel/ -~-~~-~~~-~~-~- Find Amazing Online Excel Tips and Tricks: https://trumpexcel.com/ -~-~~-~~~-~~-~- Let's Connect: Google+ ► https://plus.google.com/+Trumpexcel Facebook ► https://www.facebook.com/Trumpexcel Twitter ► https://twitter.com/TrumpExcel Pinterest ► https://in.pinterest.com/trumpexcel/ TrumpExcel Channel: https://www.youtube.com/c/trumpexcel
Views: 525008 Trump Excel
Excel Statistics 31: Histogram using Data Analysis Add-in
 
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See how to create a Frequency Distribution, a Cumulative Freqency Distribution, a Histogram Chart and an Ogive Chart with the Data Analysis Add-in. Chapter 02 Busn 210 Business and Economic Statistics and Excel Class This is a beginning to end video series for the Business & Economics Statistics/Excel class, Busn 210 at Highline Community College taught by Michael Gel Excelisfun Girvin
Views: 157317 ExcelIsFun
Data Analysis with Python for Excel User Part 1  Read and Write Excel File using Pandas
 
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Data Analysis with Python for Excel User Part 1 Read and Write Excel File using Pandas In this video we are going to learn how to read excel file using pandas Python is a widely used high-level, general-purpose, interpreted, dynamic programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than possible in languages such as C++ or Java. The language provides constructs intended to enable writing clear programs on both a small and large scale. Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles.It also supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed. The next part: https://youtu.be/-QKaVu_ebVY If you want to code in python for excel which the syntax is similar to VBA, you can go to this playlist: https://www.youtube.com/playlist?list=PL902m_5hKTbyJ4tnM0ax-7AI7VePas2QS Our money manager android app: https://play.google.com/store/apps/details?id=com.leazzy.moneymanagerleazzy
Views: 59872 Peasy Tutorial
Why Use R? - R Tidyverse Reporting and Analytics for Excel Users
 
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https://www.datastrategywithjonathan.com Free YouTube Playlist https://www.youtube.com/playlist?list=PL8ncIDIP_e6vQ0uQofezvKv3yPnL5Unxe From Excel To Big Data and Interactive Dashboard Visualizations in 5 Hours If you use Excel for any type of reporting or analytics then this course is for you. There are a lot of great courses teaching R for statistical analysis and data science that can sometimes make R seem a bit too advanced for every day use. Also since there are many different ways of using R that can often add to the confusion. The reality is that R can be used to make your every day reporting analytics that you do in Excel much faster and easier without requiring any complex statistical techniques while at the same time giving you a solid foundation to expand into those areas if you so wish. This course uses the Tidyverse standards for using R which provides a single, comprehensive and easy to understand method for using R without complicating things via multiple methods. It's designed to build upon the the skills you are already familiar with in Excel to shortcut your learning journey. If you're looking to learn Advanced Excel, Excel VBA or Databases then you need to check out this video series. In this videos series, I will show you how to use Microsoft Excel in different ways that will make you far more effective at working with data. I'm also going to expand your knowledge beyond Excel and show you tips, tricks, and tools from other top data analytics tools such as R Tidyverse, Python, Data Visualisation tools such as Tableau, Qlik View, Qlik Sense, Plotly, AWS Quick Sight and others. We'll start to touch on areas such as big data, machine learning, and cloud computing and see how you can develop your data skills to get involved in these exciting areas. Excel Formulas such as vlookup and sumifs are some of the top reasons for slow spreadsheets. Alternatives for vlookup include power query (Excel 2010 and Excel 2013) which has recently been renamed to Get and Transform in Excel 2016. Large and complex vlookup formulas can be also done very efficiently in R. Using the R Tidyverse libraries you can use the join functions to merge millions of records effortlessly. In comparison to Excel Vlookup, R Tidyverse Join can pull on multiple columns all at the same time. Microsoft Excel Power Query and R Tidyverse Joins are similar to the joins that you do in databases / SQL. The benefit that they have over relational databases such as Microsoft Access, Microsoft SQL Server, MySQL, etc is that they work in memory so they are actually much faster than a database. Also since they are part of an analytics tool instead of a database it is much faster and easier to build your analysis and queries all in the same tools. My very first R Tidyverse program was written to replace a Microsoft Access VBA solution which was becoming complicated and slow. Note that Microsoft Access is very limited in analytics functions and is missing things as simple as Median. Even though I had to learn R programming from scratch and completely re-write the Microsoft Access VBA solution it was so much easier and faster. It blew my mind how much easier R programming with R Tidyverse was than Microsoft Access VBA or Microsoft Excel VBA. If you have any VBA skills or are looking to learn VBA you should definitely checkout my videos on R Tidyverse. To understand why R Tidyverse is so much easier to work with than VBA. R Tidyverse is designed to work directly with your data. So If you want to add a calculated column that’s around one line of script. In Excel VBA, the VBA is used to control the DOM (Document Object Model). In Excel that means that you VBA controls things like cells and sheets. This means your VBA is designed to capture the steps that you would normally do manually in Microsoft Excel or Microsoft Access. VBA is not actually designed to work directly with your data. Note the most efficient path is to reduce the data pulled down from the database in the first place. This is referring to the amount of data you are pulling down from your data warehouse or data lake. It makes no sense to pull data from a data warehouse / data lake to pull into another database to query add joins / lookups to then pull it into Excel or other analysis tool. Often analyst build these intermediate databases because they either don’t have control of the data warehouse or they need to join additional information. All of these operations are done significantly faster in a tool such as R Tidyverse or Microsoft Excel Power Query.
Views: 16092 Jonathan Ng
Data Analysis with Excel
 
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Analyze data using Excel. Use standard deviation, make a graph with a trendline, include error bars, determine the uncertainty in the slope and y-intercept using LINEST.
Views: 248602 WCEastFZX
Excel - One-Way ANOVA      Analysis Toolpack
 
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Many more great Excel tutorials linked below: http://www.youtube.com/playlist?list=PL8004DC1D703D348C&feature=plcp Be sure to watch my other Excel tutorial videos on my channel, including more advanced techniques and many useful and practical ones. Be sure to Subscribe and Comment. Technically you should say Fail to Reject Ho because you have determined there is a lack of evidence against Ho. You have not proven Ho in any significant way. With that said, many introductory courses teach students that they can conclude that we Accept Ho. Please be aware of the nuance regardless of how you choose to phrase the conclusion. Reject Ho, however, is a stronger statement that we can justifiably make using the laws of probability and the level of significance of the test. When we Reject Ho we are concluding that there is enough evidence against Ho with the state level of significance used. We are willing to accept the chance of making a Type I Error, but we are very clear about the probability of its occurrence, i.e., it is equal to alpha (at least nominally).
Views: 293806 Jalayer Academy
Part 1 - Using Excel for Open-ended Question Data Analysis
 
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Completing data analysis on open-ended questions using Excel. For analyzing multiple responses to an open-ended question see Part 2: https://youtu.be/J_whxIVjNiY Note: Selecting "HD" in the video settings (click on the "gear" icon) makes it easier to view the data entries
Views: 172017 Jacqueline C
How to Calculate a Correlation in Microsoft Excel - Pearson's r
 
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Check out our brand-new Excel Statistics Text: https://www.amazon.com/dp/B076FNTZCV How to Calculate the Correlation using the Data Analysis Toolpak in Microsoft Excel is Covered in this Video (Part 1 of 2). Correlation in Excel Data Analysis Toolpak Pearson's r in Excel Statistics in Excel Video Transcript: In this video we'll take a look at how to calculate the correlation coefficient in Microsoft Excel. Now on your screen here we have two variables hours studied and that indicates the number of hours studied for an exam and then exam grade which is just a percentage grade on an exam. Now we want to calculate the correlation between these two variables to see if there's a relationship there. So do that we want to go to Data and then select Data Analysis and here we want to select Correlation and then click OK and then for Input Range what we want to do here is select all of our values and I'm going to go ahead and select the variable names as well. So click the mouse and hold the mouse button down and select all the cells there and I want to be sure since I did select the variable names or labels that I check the Labels in First Row box then click OK and then here I'm going to go ahead and expand this a little bit because it's quite small and then we'll go and round this down as well. OK so that's our correlation. I can also put it right here it's the same thing so let's take a look at what this is here. So the correlation between exam grade and our study is .86 so we could say r for Pearson's r equals .86. Now that indicates a very strong positive correlation between number of hours studied and the grade on the exam. So in other words the way we would interpret a positive correlation is people who studied more hours tended to do better on the exam and people who studied fewer hours tended to do worse on the exam. Now the relationship isn't perfect but it is very strong in this example. Now in our next video we'll test this value .86 to see whether it's significantly different from zero. YouTube Channel: https://www.youtube.com/user/statisticsinstructor Channel Description: For step by step help with statistics, with a focus on SPSS (with Excel videos now too). Both descriptive and inferential statistics covered. For descriptive statistics, topics covered include: mean, median, and mode in spss, standard deviation and variance in spss, bar charts in spss, histograms in spss, bivariate scatterplots in spss, stem and leaf plots in spss, frequency distribution tables in spss, creating labels in spss, sorting variables in spss, inserting variables in spss, inserting rows in spss, and modifying default options in spss. For inferential statistics, topics covered include: t tests in spss, anova in spss, correlation in spss, regression in spss, chi square in spss, and MANOVA in spss. New videos regularly posted. Videos series coming soon include: multiple regression in spss, factor analysis in spss, nonparametric tests in spss, multiple comparisons in spss, linear contrasts in spss, and many more. Subscribe today! YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Views: 136365 Quantitative Specialists
Excel vs Python vs R for Data Analysis. Making the right pick
 
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There is a lot of textbook arguments on Excel vs Python vs R. In fact, a few weeks back I used to be part of that argument. I took sides with Excel. And I had my solid reasons. But now I don't take sides anymore. I focus on a bigger picture, a picture I became aware of only after I transitioned for reading textbooks and doing video tutorials on Python and R to carrying out live interesting projects with them. In this webinar I will be sharing my experience on using them all and what practical insight you too need to have to move from those textbook arguments to seeing the big picture. And most importantly, I will be showing you that big picture. You shouldn't miss this webinar. Time: 3:00pm to 4:00pm Date: Tuesday, 21 March 2017 Venue: YouTube Live See you!
Views: 6599 Michael Olafusi
Excel Statistics 08: Install Excel 2007 Data Analysis Add-in
 
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Download Excel Files: Start File: https://people.highline.edu/mgirvin/AllClasses/210M/Content/ch00/Busn210Ch00IntroToExcel.xlsm Finished File: https://people.highline.edu/mgirvin/AllClasses/210M/Content/ch00/Busn210Ch00IntroToExcelFinished.xlsm Full Page With All File Links: http://people.highline.edu/mgirvin/excelisfun.htm See how to Install Data Analysis Add-in using Excel Options and the Add-in Feature. This is a beginning to end video series for the Business & Economics Statistics/Excel class, Busn 210 at Highline Community College taught by Michael Gel ExcelIsFun Girvin
Views: 228447 ExcelIsFun
Excel 2013 Statistical Analysis #06: Frequency Distributions & Column Charts, Categorical Variables
 
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Download files: http://people.highline.edu/mgirvin/excelisfun.htm This video covers how to create Frequency Distributions and Appropriate Charts for Categorical Data using Formulas, PivotTables, Column Charts, Bar Charts and Pie Charts: 1. (00:32) Overview with diagram of tables and charts we will create in this video 2. (01:01) Notes in Workbook that you can print out and read 3. (02:05) Define Frequency Distribution 4. (03:55) Frequency Distribution create from Cell Phone Sales Data 5. (04:00) Advanced Filter to get a Unique List for Frequency Distribution 6. (05:55) Using COUNTIFS function to Create Frequency Distribution 7. (07:00) Formulas to create Relative Frequency 8. (09:36) TRUNC function to show that Number Formatting does NOT remove decimals 9. (11:00) Why Relative Frequencies add up to 1: Collectively Exhaustive and Mutually Exclusive Categories 10. (11:20) Formulas to create Percent Frequency with Number Formatting 11. (13:24) Formulas to create Percent Frequency with Times 100 12. (14:54) Add Borders using Format Cells Dialog Box: Solid Top Border and Double Bottom Border 13. (16:38) Use PivotTable to create Frequency Distribution 14. (17:38) Create Relative Frequency & Percent Frequency using the “Show Values As” feature and the “% of Column Total” option 15. (19:30) Compare and Contrast Formulas and PivotTables 16. (21:09) Column Chart for Frequency Distribution with Categorical Data 17. (23:59) Column Chart for Percent Frequency Distribution with Categorical Data 18. (25:10) Bar Chart for Frequency Distribution with Categorical Data 19. (25:44) Pie Chart for Percent Frequency Distribution with Categorical Data 20. (27:30) Chart from PivotTable with Many Columns of Calculations (Trouble) 21. (28:57) Create Individual PivotTables and PivotCharts to solve “Trouble”. Frequency Distribution create from Boomerang Product Sales Data. 22. (31:11) Discrete Quantitative Data (Numbers) should be charted with a Column that has Gaps. 23. (31:55) Pareto Chart Tabular & Graphical Displays For Categorical Variables
Views: 48671 ExcelIsFun
Pivot Tables in Excel for Data Analysis and Decision Making
 
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A manager of a travel agency with a tight budget wishes to target his already existing clients with brochures so that he gets maximum response. The analysis of the data with Pivot Tables in Excel leads to an elegant solution. Some more interesting details available here: http://www.familycomputerclub.com/excel/how-to-create-pivot-tables-in-excel-2007.html
Views: 7291 Dinesh Kumar Takyar
Part 2: Using Excel for Open-ended Question Data Analysis
 
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This is Part 2 of Using Excel for Open-ended Question Data Analysis and addresses the question posted by several viewers - how to analyze multiple responses in open-ended questions. Part 1 is available here: https://www.youtube.com/watch?v=yWBXV651yd4
Views: 14606 Jacqueline C