February SMI Training: Data Visualization. prepared by MEMconsultants February 10, 2016

Transcription

1 February SMI Training: Data Visualization prepared by MEMconsultants February 10, 2016

2 Agenda Introductions Basic Descriptive Statistics Best Practices in Data Visualization How to Use Pivot Tables Closing and Questions

3 Managing Expectations This presentation will give an overview of basic principles and best practices. This presentation will not make you experts in data visualization and/or Excel. We are assuming a wide variety of skills in the room: If you are comfortable using Excel and already know the information being covered, partner up with someone who looks lost and help them. If you are lost, ask questions someone else is thinking the same thing!

4 About Your Data Use Who looks at your data (besides you)? What software do you use for data analysis?

5 Basic Descriptive Statistics

6 What are Descriptive Statistics? Descriptive Statistics numbers that are used to summarize and describe data Inferential Statistics converting information about a sample into intelligent guesses about the population. Examples of Descriptive Statistics Total 483 students from 6 programs completed the survey Mean or Average 80 responses per program Median 39 responses per program Range 14 to 267 responses per program Percentages 55% of responses from students in CAN

7 Accessing Data Creating a template for data entry Using Excel, create one column for each survey question Make each survey collected in its own row Create codes to convert words to numbers Downloading from your SurveyMonkey account Analyze Results tab Export All Individual Responses Download as Excel file If results are in YDEKC s SurveyMonkey account, contact Sarah to receive your data.

8 Calculating Descriptive Statistics in Excel Use Find and Replace to convert words to numbers Useful formulas for analysis =SUM(range) =AVERAGE(range) =COUNT(range) =COUNTIF(range,criteria) Use $ to lock cells Switch to Excel for tutorial

9 Best Practices in Data Visualization

10 What does this chart tell you? YTP RAYS One Song, One Chance New Futures Not at All Somewhat Mostly Completely One World Now CAN 0% 20% 40% 60% 80% 100%

11 What does this chart tell you? Eight out of ten students agree I don t give up easily completely or mostly. New Futures 56% 25% 19% YTP 43% 33% 15% 9% One Song, One Chance 36% 50% 14% RAYS 34% 40% 20% 6% CAN 33% 45% 18% 3% One World Now 16% 63% 21% Completely Mostly Somewhat Not at All

12 Tips for Telling Your Story Simplify! Remove border Remove grid lines Remove axes Remove legend Remove title Remove color Category 4 Category 3 Category 2 Category 1 Chart Title Series 3 Series 2 Series

13 Tips for Telling Your Story Default Chart Simplified Chart Category 4 Chart Title Category 4 Category 3 Category 2 Series 3 Series 2 Series 1 Category 3 Category 2 Category 1 Category

14 Tips for Telling Your Story Emphasize Add labels Add descriptive title and subtitle Format text Add color for emphasis or branding Fourth Graders attend most frequently. Seventh graders have the lowest attendance rate. Category 4 th Grade 4 Category 5 th Grade 3 Category 6 th Grade 2 Medium Low High Category 7 th Grade 1

15 Chart Example Make your chart match Anne s. Insert clustered bar chart. Sort data by All Grantees average Simplify remove border, gridlines, axes, legend, title, color Emphasize add labels, descriptive title and color; format text Switch to Excel for tutorial and practice

16 How to Use Pivot Tables

17 Pivot Tables Used to look at data by groups (crosstab) Do responses differ by program? Do different groups of students respond differently?

18 Pivot Table Example Select data in cells A1:L479 Insert Pivot Table on new worksheet Drag and drop Attend to Row Labels Drag and drop MS_GiveUp to Values Change Sum to Average Reduce to two decimal points for ease of comparison Switch to Excel for tutorial and practice

19 Closing and Questions

20 Questions from Survey How to create validity using data visualization? How to decide whether a sample size can be considered representative of the whole group? Descriptive vs. Inferential statistics Top 5 things to pay attention to when setting up a quantitative analysis We have become accustomed to thinking that funders always prefer this method, but is that universally true? What if the data isn't meaningful?

21 Unanswered Questions Try to leave plenty of time for this so that participants can ask about specific issues they are facing.

22 Ann Emery Resources Word Clouds tagxedo.com wordle.net

23 The End Thank you