By: Darin Johnson, Linda Gorton, Bekka Rigby & Sara Cataldo - - PowerPoint PPT Presentation

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By: Darin Johnson, Linda Gorton, Bekka Rigby & Sara Cataldo - - PowerPoint PPT Presentation

By: Darin Johnson, Linda Gorton, Bekka Rigby & Sara Cataldo Slide 3 Research Topic & Data Collection Plan Slide 4 Graph & Variable Data (Cups of Coffee on Average Per Day) Slide 5 Graph & Variable Data


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SLIDE 1

By: Darin Johnson, Linda Gorton, Bekka Rigby & Sara Cataldo

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SLIDE 2

 Slide 3 – Research Topic & Data

Collection Plan

 Slide 4 – Graph & Variable Data (Cups

  • f Coffee on Average Per Day)

 Slide 5 – Graph & Variable Data (Hours

  • f Sleep on Average Per Night)

 Slide 6 – Graph Comparing the

Variables

 Slide 7 – Results & Conclusions  Final Slide – List of Group Members &

Their Contributions

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SLIDE 3

"For adult women, is number of cups of

coffee per day related to hours of sleep?"

Data Collection – Systematic sample; start at a public location. Interview every 3rd woman, starting with the 3rd woman until reach 100 particpants.

Interview Questions: 1.Would you be willing to answer a few quick questions regarding sleep and coffee? 2.Are you 18 years old or older? If yes proceed to question 3.

  • 3. Do you live in Utah? If yes proceed to Question 4.
  • 4. Do you drink coffee? If yes move on to complete the rest of the questions. If no on

any of the first four questions, go to the next potential subject. 5.How many cups of coffee do you drink on an average day? 6.How many hours of sleep do you get on an average day?

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SLIDE 4

General Summary Count Mean IQR St. Dev. Variance Range Mode Outliers 100 2.698 1.75 1.574 2.479 9.7 2 8,10 Five number Summary Min 25th% Median 75th% Max 0.3 1.75 2.5 3.5 10

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SLIDE 5

General Summary Count Mean

  • St. Dev. Variance Range IQR Mode Outliers

10 07.15 1.222 1.492 6.5 2 7 None Five Number Summary Min 25th% Median 75th% Max 4.5 6 7 8 11

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SLIDE 6

Line of regression equation: y = - 0.17612x + 7.6251 Linear Correlation Coefficient ( R ) =- 0.227

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SLIDE 7

Results and Conclusions

  • Is the amount of coffee drank per day related to the amount of

sleep women get per day?

  • The negative slope on the regression line supports the inverse

correlation between the variables.

  • An R value of -0.227 indicates that the variables fluctuate in
  • pposite directions.
  • Knowing the physiologic effects of caffeine on the human body.

Supported by the data we can conclude that, increased coffee consumption especially in high amounts correlates to less hours of sleep per night.

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SLIDE 8

Contributing group members

Sara Cataldo- Slides 1-2 Linda Gorton- Slides 4-6 Darin Johnson- Slide 7 and compilation of presentation Bekka Rigby- Slide 3