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The Data Analysis Process
 
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The process of doing statistical analysis follows a clearly defined sequence of steps whether the analysis is being done in a formal setting like a medical lab or informally like you would find in a corporate environment. This lecture gives a brief overview of the process.
Views: 36910 White Crane Education
Qualitative analysis of interview data: A step-by-step guide
 
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The content applies to qualitative data analysis in general. Do not forget to share this Youtube link with your friends. The steps are also described in writing below (Click Show more): STEP 1, reading the transcripts 1.1. Browse through all transcripts, as a whole. 1.2. Make notes about your impressions. 1.3. Read the transcripts again, one by one. 1.4. Read very carefully, line by line. STEP 2, labeling relevant pieces 2.1. Label relevant words, phrases, sentences, or sections. 2.2. Labels can be about actions, activities, concepts, differences, opinions, processes, or whatever you think is relevant. 2.3. You might decide that something is relevant to code because: *it is repeated in several places; *it surprises you; *the interviewee explicitly states that it is important; *you have read about something similar in reports, e.g. scientific articles; *it reminds you of a theory or a concept; *or for some other reason that you think is relevant. You can use preconceived theories and concepts, be open-minded, aim for a description of things that are superficial, or aim for a conceptualization of underlying patterns. It is all up to you. It is your study and your choice of methodology. You are the interpreter and these phenomena are highlighted because you consider them important. Just make sure that you tell your reader about your methodology, under the heading Method. Be unbiased, stay close to the data, i.e. the transcripts, and do not hesitate to code plenty of phenomena. You can have lots of codes, even hundreds. STEP 3, decide which codes are the most important, and create categories by bringing several codes together 3.1. Go through all the codes created in the previous step. Read them, with a pen in your hand. 3.2. You can create new codes by combining two or more codes. 3.3. You do not have to use all the codes that you created in the previous step. 3.4. In fact, many of these initial codes can now be dropped. 3.5. Keep the codes that you think are important and group them together in the way you want. 3.6. Create categories. (You can call them themes if you want.) 3.7. The categories do not have to be of the same type. They can be about objects, processes, differences, or whatever. 3.8. Be unbiased, creative and open-minded. 3.9. Your work now, compared to the previous steps, is on a more general, abstract level. 3.10. You are conceptualizing your data. STEP 4, label categories and decide which are the most relevant and how they are connected to each other 4.1. Label the categories. Here are some examples: Adaptation (Category) Updating rulebook (sub-category) Changing schedule (sub-category) New routines (sub-category) Seeking information (Category) Talking to colleagues (sub-category) Reading journals (sub-category) Attending meetings (sub-category) Problem solving (Category) Locate and fix problems fast (sub-category) Quick alarm systems (sub-category) 4.2. Describe the connections between them. 4.3. The categories and the connections are the main result of your study. It is new knowledge about the world, from the perspective of the participants in your study. STEP 5, some options 5.1. Decide if there is a hierarchy among the categories. 5.2. Decide if one category is more important than the other. 5.3. Draw a figure to summarize your results. STEP 6, write up your results 6.1. Under the heading Results, describe the categories and how they are connected. Use a neutral voice, and do not interpret your results. 6.2. Under the heading Discussion, write out your interpretations and discuss your results. Interpret the results in light of, for example: *results from similar, previous studies published in relevant scientific journals; *theories or concepts from your field; *other relevant aspects. STEP 7 Ending remark This tutorial showed how to focus on segments in the transcripts and how to put codes together and create categories. However, it is important to remember that it is also OK not to divide the data into segments. Narrative analysis of interview transcripts, for example, does not rely on the fragmentation of the interview data. (Narrative analysis is not discussed in this tutorial.) Further, I have assumed that your task is to make sense of a lot of unstructured data, i.e. that you have qualitative data in the form of interview transcripts. However, remember that most of the things I have said in this tutorial are basic, and also apply to qualitative analysis in general. You can use the steps described in this tutorial to analyze: *notes from participatory observations; *documents; *web pages; *or other types of qualitative data. STEP 8 Suggested reading Alan Bryman's book: 'Social Research Methods' published by Oxford University Press. Steinar Kvale's and Svend Brinkmann's book 'InterViews: Learning the Craft of Qualitative Research Interviewing' published by SAGE. Good luck with your study. Text and video (including audio) © Kent Löfgren, Sweden
Views: 642097 Kent Löfgren
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: 393774 ExcelIsFun
Interview with a Data Analyst
 
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This video is part of the Udacity course "Intro to Programming". Watch the full course at https://www.udacity.com/course/ud000
Views: 269319 Udacity
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: 1451910 ExcelIsFun
How To Analyze Facebook Advertising Data. Learn What Facebook Ad Manager Data Means & How To Scale
 
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Setting up the Facebook advertising campaign is easy... Analyzing the data and knowing if you have a profitable or failing campaign is tough... See exactly how I analyze my Facebook ads data, now! There are follow up videos to this one where I continue to grow this campaign with more $5 facebook ad sets and also analyze the different interests and ad sets. Check out the next one in the series, here: https://www.youtube.com/watch?v=Fp5CMGO64dM&index=2&list=PL0sOKzn__yK1uMYzAwJwIMMT5WDF46Qcl Last Monday I published a video where I show you how I setup a full Facebook retargeting ad campaign. I also added a second facebook ad campaign based on a look alike to show you how easy it is to set up multiple advertising campaigns in Facebook. If you missed it, that video is here: https://www.youtube.com/watch?v=DluuQ952900 The second Facebook ad campaign is an explanation of "how to run a $5 per day facebook ad campaign" where I show you how easy it is when duplicating out the ad sets... This video covers that approach and theory for $5 facebook ads in more detail: https://www.youtube.com/watch?v=fceh6_UZz8A This video now looks into the data and helps you understand how I monitor and adapt to what happened in Facebook from the advertisement. I explain not only what to do, but what I'm thinking and also what I'm looking at ad monitoring to make sure that my Facebook ads are in the right place. I explain the parameters for when I scale my facebook ads and when I turn them off. I cover the most important metrics to track, which are covered deeper in this video: https://www.youtube.com/watch?v=YVOEcxIZ7u0 If you want more content about Facebook advertising, check out my free case study where I show you how I generated about 14,000 leads in
Views: 23308 Miles Beckler
Types of Data: Nominal, Ordinal, Interval/Ratio - Statistics Help
 
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The kind of graph and analysis we can do with specific data is related to the type of data it is. In this video we explain the different levels of data, with examples. Subtitles in English and Spanish.
Views: 749474 Dr Nic's Maths and Stats
Data Collection & Analysis
 
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Impact evaluations need to go beyond assessing the size of the effects (i.e., the average impact) to identify for whom and in what ways a programme or policy has been successful. This video provides an overview of the issues involved in choosing and using data collection and analysis methods for impact evaluations
Views: 51201 UNICEF Innocenti
Data Collection: Understanding the Types of Data.
 
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Data falls into several categories. Each type has some pros and cons, and is best suited for specific needs. Learn more in this short video from our Data Collection DVD available at http://www.velaction.com/data-collection-lean-training-on-dvd/.
Views: 130379 VelactionVideos
Data Analytics for Beginners | Introduction to Data Analytics | Data Analytics Tutorial
 
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Data Analytics for Beginners -Introduction to Data Analytics https://acadgild.com/big-data/data-analytics-training-certification?utm_campaign=enrol-data-analytics-beginners-THODdNXOjRw&utm_medium=VM&utm_source=youtube Hello and Welcome to data analytics tutorial conducted by ACADGILD. It’s an interactive online tutorial. Here are the topics covered in this training video: • Data Analysis and Interpretation • Why do I need an Analysis Plan? • Key components of a Data Analysis Plan • Analyzing and Interpreting Quantitative Data • Analyzing Survey Data • What is Business Analytics? • Application and Industry facts • Importance of Business analytics • Types of Analytics & examples • Data for Business Analytics • Understanding Data Types • Categorical Variables • Data Coding • Coding Systems • Coding, coding tip • Data Cleaning • Univariate Data Analysis • Statistics Describing a continuous variable distribution • Standard deviation • Distribution and percentiles • Analysis of categorical data • Observed Vs Expected Distribution • Identifying and solving business use cases • Recognizing, defining, structuring and analyzing the problem • Interpreting results and making the decision • Case Study Get started with Data Analytics with this tutorial. Happy Learning 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: 184310 ACADGILD
How to Analyze Satisfaction Survey Data in Excel with Countif
 
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Purchase the spreadsheet (formulas included!) that's used in this tutorial for $5: https://gum.co/satisfactionsurvey ----- Soar beyond the dusty shelf report with my free 7-day course: https://depictdatastudio.teachable.com/p/soar-beyond-the-dusty-shelf-report-in-7-days/ Most "professional" reports are too long, dense, and jargony. Transform your reports with my course. You'll never look at reports the same way again.
Views: 332634 Ann K. Emery
Facebook Reports & Advertising Data Analysis - Crushing E-Commerce - Lesson 17
 
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In this video, I discuss how to check your Facebook advertising stats. To check out the full course, click here: http://kingpinning.com/crushing-e-commerce/
Views: 8562 Kingpinning
Analytical Reports: Writing Analytical Reports
 
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This video introduces students to Analytical Reports, which are a common form of communication in the technical workplace. These reports present research addressing a specific problem or research question. The typical arrangement of an Analytical Report contains the following sections: Introduction, Methods, Results and Discussion (the IMRaD pattern). In this video, these sections are discussed by highlighting examples from a student report.
Views: 23284 umnWritingStudies
R Markdown for a Data Analysis Report
 
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Guide for my students on producing data analysis reports using R Markdown in the R Studio IDE.
Views: 13201 Homer White
Comprehensive Power BI Desktop Example: Visualize Excel Data & Build Dynamic Dashboard (EMT 1360)
 
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Download File: http://people.highline.edu/mgirvin/excelisfun.htm See how to use Power BI Desktop to import, clean and transform Sales Tables from Multiple Excel Files and consolidate into a Single Proper Data Set that can be linked in a Relationship to other tables, and then build DAX Calculated Columns & Measures for Gross Profit that can be used in a Dynamic Dashboard with Map, Column Chart, Line Chart, Card and Slicer visualizations. During the whole process we will compare and contrast how the process is similar and different from Excel’s Power Query and Power Pivot DAX. The steps we will see in this video are: 1. (00:17) Introduction to entire process for Power BI Desktop, including looking at the finished Dashboard 2. (04:50) Import Multiple Excel Files From Folder 3. (05:44) Name Query 4. (06:02) Transform extension column to lowercase 5. (06:34) Filter Files to only include “.xlsx” file extensions 6. (07:05) Remove Columns 7. (07:18) November 2016 Power Query Update Problem 8. (08:05) Add Custom Column with Excel.Workbook Function to extract the Excel Objects from each File. 9. (09:40) Delete Content Column 10. (10:41) Filter to only include Excel Sheet Objects 11. (11:06) Filter to exclude sheets that contain the word “Sheet” 12. (11:40) Remove Columns 13. (11:51) Expand Data and Sheet Name Columns 14. (12:06) Change Field Names 15. (12:22) Change Data Types 16. (14:05) Add Custom Column to calculate Net Revenue Column then round Number.Round function. Then Add Fixed Decimal Data Type. 17. (15:59) Remove columns for Amount and Revenue Discount 18. (16:10) Close and Apply to add to Data Model 19. (17:05) Import Excel Manager Table. Change Data Types to Text. Close and Apply 20. (18:10) Create Relationship between Zip Code Columns 21. (19:03) Create DAX Calculated Column with the IF Function to Categorize Retail Data. Change Data Type. 22. (21:53) Create DAX Measures for: Total Revenue, Total COGS and Gross Profit. Add Currency Number Formatting with No Decimals Showing. 23. (24:28) Create DAX Measures for: Gross Profit Percentage. Add Percentage Number Formatting with Two Decimals Showing. 24. (25:35) Create Map Visualization for Zip Code & Gross Profit Data (Zip Code with relationship to Managers) 25. (26:20) Create Clustered Bar for Manager Names & Gross Profit Data (Zip Code with relationship to Managers) 26. (27:15) Create Clustered Column for Product & Gross Profit Data, with a Line Chart for Gross Profit Percentage 27. (28:19) Create Clustered Column for Payment Method & Gross Profit Data, with a Line Chart for Gross Profit Percentage 28. (28:45) Create Slicer for States. 29. (29:00) Create Card Visualization for Total Revenue, Total COGS, Gross Profit and Gross Profit Percentage. 30. (29:57) Summary Learn Power BI Desktop Basics. Introduction to Power BI Desktop. Getting Started with Power BI Desktop. Create Impactful Reports With Power BI Desktop. Microsoft Power BI.
Views: 105916 ExcelIsFun
How to create an interactive reporting tool in Excel
 
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Microsoft Certified Trainer Melissa Esquibel shows you how to slice and dice data and present it in an attractive visual package.
Data Collection Methods
 
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This video was completed as part of a Masters project in DCU. It is the Introduction to a series of videos on Data Collection Methods
Views: 84102 Scott Crombie
How to Analyze Sales Data with Excel
 
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Learn how to analyze product sales data using Excel features like pivot tables and charts. For more info. pls. visit http://chandoo.org/wp/2010/09/22/analyzing-product-launch-sales/
Quick Data Analysis with Google Sheets | Part 1
 
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Spreadsheet software like Excel or Google Sheets are still a very widely used toolset for analyzing data. Sheets has some built-in Quick analysis features that can help you to get a overview on your data and very fast get to insights. #DataAnalysis #GoogleSheet #measure 🔗 Links mentioned in the video: Supermetrics: http://supermetrics.com/?aff=1014 GA Demo account: https://support.google.com/analytics/answer/6367342?hl=en 🎓 Learn more from Measureschool: http://measureschool.com/products 🚀Looking to kick-start your data journey? Hire us: https://measureschool.com/services/ 📚 Recommended Measure Books: https://kit.com/Measureschool/recommended-measure-books 📷 Gear we used to produce this video: https://kit.com/Measureschool/measureschool-youtube-gear Our tracking stack: Google Analytics: https://analytics.google.com/analytics/web/ Google Tag Manager: https://tagmanager.google.com/ Supermetrics: http://supermetrics.com/?aff=1014 ActiveCampaign: https://www.activecampaign.com/?_r=K93ZWF56 👍 FOLLOW US Facebook: http://www.facebook.com/measureschool Twitter: http://www.twitter.com/measureschool
Views: 7657 Measureschool
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://github.com/datasciencedojo/meetup/tree/master/business_data_analysis_with_excel **Find out more about David here: https://www.meetup.com/data-science-dojo/events/236198327/ -- Learn more about Data Science Dojo here: http://bit.ly/2lF48cC -- 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: 40955 Data Science Dojo
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: 3454 Jonathan Ng
3 essential Google Analytics reports to measure your activity
 
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In this video, Sylvain, COO of SEO.fr will show you three types of Google Analytics reports designed to help you get a better grasp on your data and improve the decision-making process on your site. Contact the expert : http://bit.ly/2sgfG9o PrestaShop website: https://www.prestashop.com/ PrestaShop on Twitter: https://twitter.com/PrestaShop PrestaShop on Facebook: https://www.facebook.com/prestashop/
Views: 5187 PrestaShop Official
Introduction to Statistics..What are they? And, How Do I Know Which One to Choose?
 
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This tutorial provides an overview of statistical analyses in the social sciences. It distinguishes between descriptive and inferential statistics, discusses factors for choosing an analysis procedure, and identifies the difference between parametric and nonparametric procedures.
Views: 207186 The Doctoral Journey
SPSS for questionnaire analysis:  Correlation analysis
 
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Basic introduction to correlation - how to interpret correlation coefficient, and how to chose the right type of correlation measure for your situation. 0:00 Introduction to bivariate correlation 2:20 Why does SPSS provide more than one measure for correlation? 3:26 Example 1: Pearson correlation 7:54 Example 2: Spearman (rhp), Kendall's tau-b 15:26 Example 3: correlation matrix I could make this video real quick and just show you Pearson's correlation coefficient, which is commonly taught in a introductory stats course. However, the Pearson's correlation IS NOT always applicable as it depends on whether your data satisfies certain conditions. So to do correlation analysis, it's better I bring together all the types of measures of correlation given in SPSS in one presentation. Watch correlation and regression: https://youtu.be/tDxeR6JT6nM ------------------------- Correlation of 2 rodinal variables, non monotonic This question has been asked a few times, so I will make a video on it. But to answer your question, monotonic means in one direction. I suggest you plot the 2 variables and you'll see whether or not there is a monotonic relationship there. If there is a little non-monotonic relationship then Spearman is still fine. Remember we are measuring the TENDENCY for the 2 variables to move up-up/down-down/up-down together. If you have strong non-monotonic shape in the plot ie. a curve then you could abandon correlation and do a chi-square test of association - this is the "correlation" for qualitative variables. And since your 2 variables are ordinal, they are qualitative. Good luck
Views: 486843 Phil Chan
Data Analysis in SPSS Made Easy
 
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Use simple data analysis techniques in SPSS to analyze survey questions.
Views: 772976 Claus Ebster
Statistical Analysis Report
 
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Statistical Analysis Report on Copilot
Views: 98 Briana Keith
How to Create a Summary Report from an Excel Table
 
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One of my viewers asked for my help in creating an Executive Summary Report - because her manager will not allow her to use a Pivot Table. Here are the tips and techniques that I demonstrate in this lesson: 1) Use Excel's Advanced Filter to Extract a list of unique customer names from a filed with over 4,000 records. 2) Convert a normal range of data cells into an Excel 2007 / 2010 Table (as a List in Excel 2003) - so that range references will update automatically when you append records. 3) Create Named Ranges of Cells that you can use in Formulas & Functions. 4) Use the SUMIF, AVERAGEIF and COUNTIF Functions in the Summary Report. I invite you to visit my online shopping website - http://shop.thecompanyrocks.com - to view all of my video tutorials. Danny Rocks The Company Rocks
Views: 1042891 Danny Rocks
Writing Tip #3: Writing Qualitative Findings Paragraphs
 
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This video presents a "formula" for writing qualitative findings paragraphs in research reports. It presents the Setup-Quote-Comment model (SQC).
Aging Analysis Reports using Excel - How To
 
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In this tutorial we learnt how to conduct aging analysis using Excel with different basic formulas. Complete aging analysis tutorial with conditional formatting and sparklines: https://goo.gl/LJi5nE To practice along please download the Excel exercise book at: https://goo.gl/PzQ4eG For more Excel Tutorials visit: http://pakaccountants.com/excel/ Social: Fb: http://facebook.com/exceltoexcel/ Tw: http://twitter.com/exceltoexcel/
Views: 17404 Hasaan Fazal
Report Like a Boss Using Google Data Studio
 
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Join Data Studio Product Manager Nikhil Roy and Google Analytics Advocate Louis Gray live from Google HQ on August 17th to learn about how to design and deliver exceptional reports in Google Data Studio.
Views: 127620 Google Analytics
Quick Tips: Reporting on Optimize Data in Google Analytics
 
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In this Quick Tip video, learn how to access your Optimize data in Google Analytics and get tips on the types of analysis you can do with the experiment ID, name, and variant ID, in Google Analytics.
Views: 1560 Google Analytics
Data Analyst HandsOn SQL Beginner Training (Week1)
 
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This is the first session for Data Analysts Career path for 21st May 2016 batch. Understanding the core of RDBMS and SQL programming is one of the skills that make a good analyst. This session is focused on introducing students to IT and Relational Database Management System (RDBMS) By the end of the week you would have finished learning, and achieving the below • Getting familiar with Information Technology • Background and historical knowledge of SQL • Configuring the server environment • Connecting to the server • Creating a database If you will like to get real hands-on with SQL and Data Analytics, join other hundreds of learners in our community. Send us an email [email protected]
Views: 30873 Dare Olufunmilayo
Microsoft Power Tools for Data Analysis: Dashboards & Reports. Class Introduction Video. MSPTDA #01.
 
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Download Excel File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/Intro/001-MSPTDA-IntroToClass.xlsx Download pdf Notes: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/Intro/001-MSPTDA-IntroToClass.pdf This video introduces the topics that will be covered in this Highline College BI 348 Class: Name of Class: BI 348 – Microsoft Power Tools for Data Analysis: • Power Query • Power Pivot • DAX • Power BI Desktop • Excel For Creating: • Data Models, Reports, Dashboards and Analytics Taught by Mike excelisfun Girvin, Excel MVP 2013-2018 • A class about connecting to multiple source of data, transforming the data into a refreshable & dynamic data model, and building reports and dashboards to provide insightful and actionable information. Prerequisites for this class: • Busn 216: Excel Basics, https://www.youtube.com/playlist?list=PLrRPvpgDmw0n34OMHeS94epMaX_Y8Tu1k • Busn 218: Advanced Excel, https://www.youtube.com/playlist?list=PLrRPvpgDmw0lcTfXZV1AYEkeslJJcWNKw • Busn 210: Business Statistics, https://www.youtube.com/playlist?list=PLrRPvpgDmw0ngx_uPhvasTbOWLOztsaBj What Version of Excel: • Office 365 (updated each month) What Version of Power BI Desktop: • Free Tool we will download (update each month) Over View of Topics for the class: 1. Data Analysis / Business Intelligence terms and concepts that we will learn in this class: • Proper Data Set • Fact Table • Dimension Tables • Relationships • Star Schema • ETL • Measures • Dashboards • SQL • Data Warehousing   2. Learn how to use Excel Power Query: • Import Data from multiple sources • Clean and Transform Data • Create Data Components for Star Schema Data Models • Load Data To Excel, the Data Model and Connection Only • Replace Complicated Excel Solutions with Power Query Solution • Use the Power query User Interface to create Power Query Solutions • Learn about the Case Sensitive, Function-based M Code Language that is behind the scenes in Power Query 3. Learn how to use Excel Power Pivot: • Excel Power Pivot provides: i. Data Model where we can have multiple tables, formulas and relationships (Star Schema) ii. Columnar Database to hold "Big Data" and process quickly over that "Big Data" iii. New Formula Language called DAX: 1. Many More Calculations than in Standard PivotTable 2. Build One Formula that can work in many reports 3. Add Number Formatting to Formulas • Excel Power Pivot to: i. Replace VLOOKUP Formulas and Single Flat PivotTable Data Source with Multiple Tables, Relationships in the Data Model to create more efficient Reports & Dashboards ii. Use Power Pivot Columnar Database to hold millions of rows of data iii. DAX formulas have more Power than Standard PivotTable Calculations 4. Learn about Building Star Schema Data Models: a. Why they are important in Power Pivot and Power BI Desktop b. How to build them using: i. Power Query ii. Power Pivot iii. DAX iv. Power BI Desktop 5. Learn how to author DAX Formulas for Excel’s Power Pivot & Power BI Desktop: a. Calculated Column Formulas for Data Model b. Measure Formulas for PivotTables c. DAX Functions like SUMX, CALCULATE, RELATED, and Much More… d. Lean why we must create Explicit rather than Implicit formulas e. Learn how Row Context works in formulas f. Learn how Filter Context works in formulas g. Learn about Scalar & Table Functions h. Use DAX Studio to visualize and analyze DAX Formulas 6. Learn how to use Power BI Desktop: a. Power Query to import, clean, transform and create Star Schema Data Models b. Create Relationships c. Create DAX Formulas d. Build Interactive Visualizations e. Build Dashboards   7. Learn how to use Excel: • Spreadsheet Formulas & Functions • Standard PivotTables • Power Query • Power Pivot • Build Data Model PivotTables and the resultant Reports, Dashboards and Analytics 8. Building Refreshable, Insightful Dashboards a. Build Excel Dashboards b. Build Power BI Dashboards 9. Case Studies to practice using Power Pivot & Power BI Desktop for Reporting, Building Dashboards and Building Business Analytics Solutions Buy excelisfun products: https://teespring.com/stores/excelisfun-store
Views: 12624 ExcelIsFun
Chapter 13b: Qualitative Data Collection Delivery, Analysis, Reporting
 
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This video will help you prepare for focus groups and interviews by discussing moderator skills, troubleshooting common problems, and offering tips for how to get started with the analysis process and report results. Learn more about program evaluation for driving safety at https://www.teendriversource.org/advocacy-education/program-evaluation-for-driving-safety.
Annual Report Analysis Example, Financial Statement Analysis
 
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For details, visit: http://www.financewalk.com Annual Report Analysis Example, Financial Statement Analysis Financial statements analysis is divided in the following areas in this module : • Income Statement • Balance Sheet • Footnotes • Cash Flow Analysis • Director's report • Management Discussion and Analysis • Auditor's Report • Shareholding Pattern Reading the annual reports of the company gives the basic information about the company and the industry in which it operates. Reading this chapter would enable you to understand • Components of financial statements • How to use financial information • Importance of financial statements for security analysis Income Statement Components • Sales • Other Income  Profit from the sale of assets  Dividends ( from investments, in the shares of the other companies)  Rent (Lease rental earned from commercial buildings)  Interest( Interest received on deposits made and loans given to corporate bodies and others.) • Materials Cost ( Opening stock + Purchases made during the year - Closing stock) • Employment Costs -- ( Salaries + Wages + Bonus + Gratuity + Contribution to PF + Welfare Exps. ) • Operating and Other Expenses -- Costs incurred in running a company a) Selling Exps -- Advertising ,Sales promotion, commission paid to salesmen, cash discounts b) Administration Exps -- Rent of offices and factories,municipal taxes, insurance, repairs, printing and stationery, telephone, legal, electricity costs, other exps to administer a company c) Others -- Loss made on the sale of fixed assets, Donations made by the company
Views: 40639 FinanceWalk
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: 5679257 Excel Campus - Jon
8-10 APA Style Reporting Statistical Results
 
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After conducting a statistical analysis, you should write up the results in proper APA 6th edition style. We review some general rules for reporting significance levels and where to find results in SPSS output. Table of Contents: 00:19 - Write Up Results in APA Style
Views: 5929 RStatsInstitute
SAS Visual Analytics Demo for Retail
 
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http://www.sas.com/visualanalytics Learn how to use SAS Visual Analytics to identify customer segments and do Market Basket Analysis Reporting. SAS VISUAL ANALYTICS Get fast answers to even the most complex questions using data of any size – including big data in Hadoop. Guided exploration makes it easy. In-memory processing makes it fast. Advanced data visualization tools make it clear. Scalability makes it the perfect fit. And the price makes it within your reach. LEARN MORE ABOUT SAS VISUAL ANALYTICS http://www.sas.com/software/visual-analytics/overview.html TRY VISUAL ANALYTICS YOURSELF Browse sample reports or explore on your own with this cloud-based demo. http://www.sas.com/software/visual-analytics/demos/all-demos.html SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 75,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world The Power to Know.® VISIT SAS http://www.sas.com CONNECT WITH SAS SAS ► http://www.sas.com SAS Customer Support ► http://support.sas.com SAS Communities ► http://communities.sas.com Facebook ► https://www.facebook.com/SASsoftware Twitter ► https://www.twitter.com/SASsoftware LinkedIn ► http://www.linkedin.com/company/sas Google+ ► https://plus.google.com/+sassoftware Blogs ► http://blogs.sas.com RSS ►http://www.sas.com/rss
Views: 94556 SAS Software
Map, tables, charts and diagrams in qualitative data analysis
 
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Looks at the use of charts and tables both for data elicitation and clarification and to support the analysis of qualitative data. The lecture looks at a range of different ways of presenting qualitative data in diagrams and tables. It focuses particularly on how this can support the discovery of patterns in data. This was a lecture given to postgraduate (graduate) students at the University of Huddersfield as part of a course on Qualitative Data Analysis. To learn more about social research methods you might be interested in this new, inexpensive, postgraduate, distance learning course: MSc Social Research and Evaluation. The course is delivered entirely via the Internet. http://sre.hud.ac.uk/ Works referred to in the video include: Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: a sourcebook of new methods. Beverly Hills, CA: Sage. The tables in this video are taken from this edition, but there is a new edition: Miles, M. B., Huberman, A. M. & Saldaña, J. (2014). Qualitative data analysis: a sourcebook of new methods. 3rd Ed. Los Angeles, CA: Sage. Ritchie, J., & Lewis, J. (2003) Qualitative Research Practice: A Guide for Social Science Students and Researchers. London: Sage. There is also a new edition of this book: Ritchie, J., Lewis, J., McNaughton Nicholls, C and Ormston, R (eds) (2013) Qualitative Research Practice: A Guide for Social Science Students and Researchers. London: Sage. See also my book: Gibbs, G.R. (2007) Analyzing Qualitative Data. London: Sage. See, Chapter 6 ‘Comparative Analysis’. Credits: Sounds and music: 'Fifth Avenue Stroll' from iLife Sound Effects, http://images.apple.com/legal/sla/docs/ilife09.pdf Image: Freizeitanlage Kräwinklerbrücke, Kräwinklerbrücke in Remscheid by Frank Vincentz, Wikimedia Commons, licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
Views: 7716 Graham R Gibbs
Qualitative Data Analysis - Coding & Developing Themes
 
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This is a short practical guide to Qualitative Data Analysis
Views: 87366 James Woodall
Chris Trowbridge - Quantitative Data Analysis Report
 
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Quantitative Data Analysis Report on three video cards: ATI Radeon HD 2600XT NVIDIA GeForce 7950GX2 NVIDIA GeForce 9800GX2 using 3D Mark 06 for LAN's R' Us, a local LAN gaming store.
Views: 518 chickmagntwannab
How to Extract Data from a Spreadsheet using VLOOKUP, MATCH and INDEX
 
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When you need to find and extract a column of data from one table and place it in another, use the VLOOKUP function. This function works in any version of Excel in Windows and Mac, and also in Google Sheets. It allows you to find data in one table using some identifier it has in common with another table. The two tables can be on different sheets or even on different workbooks. There is also an HLOOKUP function, which does the same thing, but with data arranged horizontally, across rows. See the companion tutorial on Tuts+ at https://computers.tutsplus.com/tutorials/how-to-extract-data-from-a-spreadsheet-using-vlookup-match-and-index--cms-20641. By Bob Flisser.
Views: 2535456 Tuts+ Computer Skills
Google Data Studio - Gender Conversion Report - Analytics Tutorial
 
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Google Data Studio - Gender Conversion Report - Analytics Tutorial http://webandsem.com/search-engine-marketing-sem-seo/ See how we can help you get the most out of your online marketing budget. https://onlinemarketingtechs.com/blog/2017/12/13/google-data-studio-gender-conversion-report-analytics-tutorial/ Okay, so today I'm going to be showing you how to build a gender report in Google Data Studio pulling from your Google Analytics. So, let's get started. Just type Google Data Studio into Google. Pull it up. Then you can select a template, but we're going to select a blank report. Title it Gender Report. Add Data Source Now, we need to add a data source. You can select from ones that you've already connected or you will need to connect to a new one. We'll go in there and connect to Google Analytics and select the account, property, and view. Connect. Alright, you'll want to add that to the report. Click on that. But, I'm going to select one that I already have. There we go. We'll add it to the report. Date Range Alight, so we're going to start out with a date range. You're going to want to select what date you want to pull the data from. We're going to go ahead and select the date range to automatically be 30 days. You can change this on the front side to be whatever date you want. But, for now, we're going to set it to be 30 days. Gender Label Now, we're going to build out the labels. Make it a little bigger. I'm going to make it white because I want it on a blue background. I'll type in men. Make the background blue. Scorecard Now, we're going to insert a scorecard. It's automatically set to sessions. We want the sessions in there for sure. We're going to compare it to the previous period. So, this is the previous 30 days. We're going to make a little blue box around it. Filter So, I've got my sessions in there. I'm going to add a filter so it only shows from the men. I'll select include, gender is equal to male. Save. Now I have my filter. I'll go ahead and copy that. Paste. Move it over. Metrics Now, I want to select a different metric (in my metric picker) I want to select completions (goal completions). You can select any goal completions you want, but I'm going to go with all of them right now. It's a total overview. Copy that. Paste. Select the new metric. I want to know the conversion rate. There it is. Be sure we have our filters on them. There's our men category, sessions, goal completions, goal conversion rate. I'm going to select them all and copy. Paste. I'm going to change the name to women. I want to make it a specific color so I can tell the difference. You can make it any color you want. Source / Medium Gender Conversion Table Now, I'm going to make a table so I can view the different data sources and mediums that different genders come from. So, it automatically has all the sessions from the different sources, but I want to see the different sources and mediums. So I'm going to type in source and select Source / Medium. I want to know what gender it's from. So I add another dimension gender. Select metric goal completions. Select a new metric conversion rate. You can adjust them to be the right size. However you want to do it. Heatmap Now, I'm going to make a little heatmap that will show the highest numbers at the top. It will basically tell you what's preforming best for that metric. What's getting the highest numerical value. You can adjust the colors to be whatever you want. There you go. Pie Chart I'm going to add a new pie chart so we can basically see who's getting the most men or women. We want to know which ones have completed the goals. When we're working with these pie charts you can select how many different pie slices you want. This one you only have the two options because of gender. Men and women are the only options that you have. You can change the color. You can change the color of the pie slices. It's pretty fun to work with....
How to Use Google Forms to Collect Data
 
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Learn to use Google Forms to collect data from specific people by sharing the link on email or on social media. It is a 3 step process that starts with creation of form and then next step is to distribute it to the audience and third step is to collect the data. All the three steps to use Google form have been explained in this tutorial. Share this video:http://youtu.be/s94fL4g0riI common use of various question types in Google forms is given below - Text — Respondents provide short answers Paragraph text — Use this for long answers Multiple choice — Respondents select one option from among several Checkboxes — select as many options from checkboxes. Choose from a list — respondents select one option from a dropdown menu Scale — rank something along a scale of numbers (e.g., from 1 to 5) Grid — respondents select a point from a two-dimensional grid Date — People filling the form can use a calendar picker to enter a date Time — respondents select a time (either a time of day or a duration of time) You can plan events, make a survey, give quiz to students or simply collect any data on Google Forms. It can save you from lot of physical effort as the collected data automatically gets saved in the linked spreadsheet.You can insert an image or video on Google forms and also set a customize theme for your form. Google forms is a gem in the Google docs, that's free to use and has a powerful tools like regular expressions that help to validate the data.Currently, only Text, Paragraph text, Check boxes, and Grid questions have support for validation. This video tutorial also covers certain Frequently asked questions given below- Can I capture respondents email address automatically? Can I receive notification on email every time a form is submitted? Can i send a personal thank you message to the respondents? Can i use Capcha on Google Form? Harish Bali is the creator of this video, he is a social media expert and an SEO. ............................................................................................... Learn to use Regular expressions in Google forms: https://support.google.com/docs/answer/3378864?hl=en Learn useful regular expressions for data validation by Labnol.org: http://www.labnol.org/internet/regular-expressions-forms/28380/ You can watch my other video on: How to use mail merge in gmail: https://www.youtube.com/watch?v=skrGMoq_TRA How to use Google drive to share files: https://www.youtube.com/watch?v=Itn3WIhQ6NQ Follow us: Blog on Tech Guide: http://www.technofare.com/ Google Plus Technofare : https://plus.google.com/+Technofareblog/posts Google Plus Harish Bali: https://plus.google.com/+harishBali/posts Facebook: https://www.facebook.com/technofare?ref=bookmarks Subscribe to Channel: https://www.youtube.com/user/Technofare Hope you found the detailed tutorial on how to use Google forms to collect data useful. Do share it with your friends on social media.
Views: 211751 Technofare
Firstbeat Sports: How to Create a Data Analysis Report
 
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Creating a data analysis report using Firstbeat Sports software
Views: 415 Firstbeat Sports
Interactive Userform and Automated Reporting in Excel, www,excelmodeler.com
 
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This video is a recording of tool developed by Excelmodeler.com Team. We are expert in Excel Programming, VBA and any work related to Excel. We have expertise in Financial Analytics, Project Management, Simulation and Modeling of Complex Mathematical concepts, Developing Prototypes in Excel etc. Kindly refer to http://excelmodeler.com for details or contact [email protected] for details
Views: 45660 Excelmodelers