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Lesson 17: Discerning Good Data from Bad Data Design principles: Less is More: Limited capacity of working memory Colored highlighting: Direction selection.

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Presentation on theme: "Lesson 17: Discerning Good Data from Bad Data Design principles: Less is More: Limited capacity of working memory Colored highlighting: Direction selection."— Presentation transcript:

1 Lesson 17: Discerning Good Data from Bad Data Design principles: Less is More: Limited capacity of working memory Colored highlighting: Direction selection of important information

2 “After taking our e-learning course, sales people sold 3.5 more units per day” Do you buy it? Design principles: Less is More: Limited capacity of working memory Highlighting: Directing selection of important information Use of images and words E-Learning ?

3 Learning Objective: Develop a statistical tool to tell what data is believable and what data should be ignored. Design principles: Less is More: Limited capacity of working memory Highlighting: Directing selection of important information Providing learning objective: Directing selection of important info How it will help you: In future assignments you will be able to read reports about e-learning studies and see if the data is statistically significant.

4 Back to the knives: Look at the data? Design principles: Highlighting: Directing selection of important information Text & Pictures close together: Contiguity principle E-Learning Without training Average sales of 100 salespeople = 87.5 knives With training Average sales of 100 salespeople = 91 knives

5 Design principles: Highlighting: Directing selection of important information Text & Pictures close together: Contiguity principle Practice exercises: Help integration E-Learning Without training Average sales of 100 salespeople = 87.5 knives With training Average sales of 100 salespeople = 91 knives What do the averages tell us?  Training increases sales of knives  Training decreases sales of knives  Training has no impact on sales of knives

6 Have you seen data that uses averages to convince you of a point? Design principles: Give context to previous work to provide hooks for retrieval and transfer. Use this space to describe some point in your job that you have seen data that includes averages.

7 Key Take-Away 1: Averages are not the whole story. Design principles: Less is more Highlighting Provide learning objective Learning Objective 2: We need to learn about Standard Deviation (SD). = SD

8 Key Take-Away 1: Averages are not the whole story. Design principles: Less is more Highlighting Provide learning objective Learning Objective 2: We need to learn about Standard Deviation (SD). = SD

9 Design principles: Less is more Highlighting Practice and involvement for integration Two histograms of 100 numbers: Both have an average of 80? What do you see as the difference?

10 Design principles: Less is more Highlighting Standard Deviation = 2 Standard Deviation = 6 A lower standard deviation means the results are CLOSER to the average A high standard deviation means the results are further from the average

11 Design principles: Less is more Practice exercise for integration Which has the LOWER Standard Deviation? A OrB  A  B  A  B

12 Design principles: Highlighting: Directing selection of important information Text & Pictures close together: Contiguity principle E-Learning Without training Average sales of 100 salespeople = 86.9 knives SD=20 With training Average sales of 100 salespeople = 90.6 knives SD=20 Back to the knives! How does SD fit in?

13 Design principles: Keep it simple Highlighting: Directing selection of important information Practice for integration Without training Average sales of 100 salespeople = 87.5 knives SD=20 What will the histogram look like? or

14 Design principles: Keep it simple Highlighting: Directing selection of important information Practice for integration With training Average sales of 100 salespeople = 91 knives SD=20 What will the histogram look like? or

15 Design principles: Keep it simple Highlighting: Directing selection of important information With training Average sales of 100 salespeople = 91 knives SD=20 Without training Average sales of 100 salespeople = 87.5 knives SD=20 Can you tell them apart?

16 Design principles: Keep it simple Highlighting: Directing selection of important information How can we be sure? With such a big SD (20), the difference between an average of 87.5 and 91 seems insignificant.

17 Key Take-Away 2: We need a tool to tell if a difference in averages is significant. Design principles: Less is more Highlighting Provide learning objective Learning Objective 3: We need to learn about p-values. = P-Value

18 Design principles: Highlighting: Directing selection of important information Text & Pictures close together: Contiguity principle E-Learning Without training Average sales of 100 salespeople = 86.9 knives SD=20 With training Average sales of 100 salespeople = 90.6 knives SD=20 Back to the knives! What is p-value? The P-Value of this data = 0.087

19 Design principles: Highlighting: Directing selection of important information Text & Pictures close together: Contiguity principle The P-Value of this data = 0.087 This means that there is a 8.7% chance that the difference between 87.5 and 91 knives was due to chance, not the e-learning program. It is “statistically insignificant and should not be trusted. P<.05 “Statistically significant” Believable P>.05 “Statistically insignificant” Do not believe!

20 Design principles: Practice for integration Text & Pictures close together: Contiguity principle Try it out! P-value=.00034 P-value=.25 P-value=.049

21 Design principles: Exercise for retrieval and transfer to the job (student) context Bringing it Home Next class, a classmate says that by using video games, the average student improves her reasoning skills by 4% What should you ask first? What kind of video game was it? How many students did you test? What is the p-value of that data?

22 Design principles: Practice for integration Text & Pictures close together: Contiguity principle Bringing it Home What is the p-value of that data? They respond that P-value = 0.012 What should you think? Hmmm. This data does not sound so good. Wow, there is about a 1% chance this finding is due to change. That is great data!

23 Design principles: Practice for integration Text & Pictures close together: Contiguity principle Bringing it Home They respond that P-value = 0.012 What should you think? Hmmm. This data does not sound so good. Wow, there is about a 1% chance this finding is due to change. That is great data!

24 Design principles: Encourage metacognitive monitoring by self-checking Self-Check: Click how you are feeling Having a hard time with basics Want to practice Got it Averages Standard Deviation P-Values


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