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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 of important information
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“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 ?
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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.
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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
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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
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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.
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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
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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
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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?
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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
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Design principles: Less is more Practice exercise for integration Which has the LOWER Standard Deviation? A OrB A B A B
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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?
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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
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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
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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?
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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.
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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
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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
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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!
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Design principles: Practice for integration Text & Pictures close together: Contiguity principle Try it out! P-value=.00034 P-value=.25 P-value=.049
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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?
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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!
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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!
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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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