Presentation on theme: "CAFFEINE CONSUMPTION VS. HOURS OF SLEEP Amie Radtke, Julie Luckart, Drew Hanson, Sofiya Mykhalska, Melissa Young, Erin Brown."— Presentation transcript:
CAFFEINE CONSUMPTION VS. HOURS OF SLEEP Amie Radtke, Julie Luckart, Drew Hanson, Sofiya Mykhalska, Melissa Young, Erin Brown
Research Question For Salt Lake City adults aged 18 and older, are ounces of caffeinated beverages consumed throughout the day related to number of hours slept the night before?
Sampling Method Stratified Sample: - Strata: Zip codes 84109, 84105, 84106, 84102, and 84020 - 10 randomly selected individuals from each strata of varying age, gender, demographic
Data Collection Quantitative Variables: 1) Ounces of caffeinated beverage consumed in one day 2) Number of hours of sleep for corresponding night Questions asked: 1)How many ounces of caffeinated beverages did you consume yesterday? 2)How many hours of sleep did you get last night?
Results: Ounces of Caffeinated Beverage Consumed Caffeine Consumed
Statistics: Correlation Linear Correlation Coefficient: -0.0393 Line of Regression Equation: y = -0.00349x + 7.1169 Critical value with 0.05 level of significance and 48 degree of freedom: 0.288 Difference between absolute value of correlation coefficient and critical value: 0.285 Statistical significance of data collected: minimal Linear Relationship: almost nonexistent, slightly negative
For Salt Lake City adults aged 18 and older, are ounces of caffeinated beverages consumed throughout the day related to number of hours slept the night before? There were two quantitative variables for which data was collected. These included the number of ounces of caffeinated beverage each subject consumed in a day and the number of hours of sleep he or she achieved that night. After analysis of the results, we found the correlation coefficient for the two variables to be -0.0393. Using a 0.05 level of significance for a sample size of 50 and a degree of freedom of 48, the critical value was found to be 0.288. Thus, these data did not show statistical significance throughout the population, nor a linear relationship. Summary
Contributions Julie Luckart: Statistics and hours of sleep frequency histogram Drew Hanson: Caffeine consumed frequency histogram Sofiya Mykhalska: Hours of sleep box plot Melissa Young: Caffeine consumed frequency histogram Amie Radtke: Scatter plot with line of regression Erin Brown: Research components, summary, and results