An article that appeared in the British Medical Journal (2010) presented the results of a randomized experiment conducted by researcher Jeremy Groves, whose objective was to determine whether the weight of his bicycle could affect his travel time to work. On each of 56 days (from mid-January to mid-July 2010), Groves tossed a E1 coin to decide whether he would be biking to work on his carbon frame (lighter) bicycle that weighed 20.9 Ibs or on his steel frame (heavier) bicycle that weighed 29.75 lbs. He then recorded the commute time (in minutes) for each trip. Here are the summary statistics for his data: Bike Type Sample size Sample average Sample SD Carbon frame (lighter) 26 108.34 min 6.25 min Steel frame (heavier) 30 107.81 min 3.89 min In terms of investigating whether the lighter carbon frame bike will tend to have a higher or lower mean commute time compared to the heavier steel frame bike, which of the following is the correct null hypothesis? There is an association between the type of bike frame and commute time. There is no association between the type of bike frame and commute time. There is an association between days and weight of bicycle. There is no association between days and weight of bicycle.An article that appeared in the British Medical Journal (2010) presented the results of a randomized experiment conducted by researcher Jeremy Groves, whose objective was to determine whether the weight of his bicycle could affect his travel time to work. On each of 56 days (from mid-January to mid-July 2010), Groves tossed a E1 coin to decide whether he would be biking to work on his carbon frame (lighter) bicycle that weighed 20.9 Ibs or on his steel frame (heavier) bicycle that weighed 29.75 lbs. He then recorded the commute time (in minutes) for each trip. Here are the summary statistics for his data: Bike Type Sample size Sample average Sample SD Carbon frame (lighter) 26 108.34 min 6.25 min Steel frame (heavier) 30 107.81 min 3.89 min Which of the following applets would be most appropriate to use, in the context of this study? One Mean One Proportion Multiple Proportions Multiple Means Matched PairsDo children diagnosed with attention deficit/hyperactivity disorder (ADHD) have smaller brains than children without this condition? Brain scans were completed for 152 children with ADHD and 139 children of similar age without ADHD. The mean brain size for the 152 children with ADHD was 1059.4 ml with a standard deviation of 117.5 mL. The mean brain size for the 139 children without ADHD was 1104.5 ml with a standard deviation of 111.3 mL. The standard deviation of a simulated null distribution of 1,000 differences in sample mean brain sizes was 13.4 mL. Use the 2SD method to calculate an approximate 95% confidence interval for the difference in population means (ADHD - Without ADHD). iIn order to investigate whether talking on cell phones is more distracting than listening to car radios while driving, sixty-four student volunteers (from a single college class) were randomly assigned to a cell phone group or a radio group (32 students were assigned to each group). Each student "drove" a machine that simulated driving situations. While "driving" the simulator, a target would flash red at irregular intervals. Participants were instructed to press the "brake" button as soon as possible when they detected a red light. Participant response times were measured as the time between the red light appearing and pushing the brake button. While driving, the radio group listened to a radio broadcast and the cell phone group carried on a conversation on the cell phone with someone in the next room. The cell phone group had an average response time of 585.2 milliseconds (SD = 89.6), and the control group had an average response time of 533.7 milliseconds (SD = 65.3). Describe the parameter of interest in words. Mean response time under simulated driving situations O Difference in sample mean response time between drivers talking on cell phones and drivers who listen to a radio broadcast Difference in long-run mean response time between drivers talking on cell phones and drivers who listen to a radio broadcast Difference in long-run proportion of response times between drivers talking on cell phones and drivers who listen to a radio broadcast