Part 2: What is the probability that a person saw results, given they received the Power Pill? What is the probability that a person saw results, given they received a placebo? Explain in terms of the study. According to the graph, when all the grades are together, 22/40=55% of the people saw results in the power pill. 100-55=45. 45% saw no results. In each grade, starting with grade A, with 60%, B with 70%, C with 50%, and D with 40%. In grade A and B, (6+7)/20= 65% saw results in the power pill, because only grade A and B had power pills. In grade C and D, (5+4)/20=45% saw results with placebo pill. Part 3:What is the probability that a person received the placebo, given that they did not see results? What is the probability that a
1. Suppose a researcher wants to design a new study with a power of 0.8 and a significance of 0.05 to test whether the caffeine content for a brand of coffee is really 100mg. A previous study gave a mean caffeine level for this brand of 110 mg and a standard deviation of 7 mg. Use PROC POWER to determine how many cups of coffee need testing.
D-The patient reports she is stable on her current dose and haven't experienced any withdrawals and/or cravings. The patient further mentioned that work is going okay, but still exploring other job opportunities. This writer provided positive feedback towards the patient's recovery process. In addition, the patient reports she has to do a pneumonia test as it was suggested by her PCP today. This writer requested for the patient to detailed if she's experiencing any symptoms and would like to consult with the clinic medical doctor. Based on the patient, she reports she was experiencing some backaches, but now, feels okay. During the remainder of the session, the patient discussed her plans for the Easter holiday and also shared with this writer that today is her son birthday.
From G*Power it explains, the sample size will be significant and good sample size. I used alpha .05 and .80 for power then I added my population size in the program (Faul, Erdfelder, Lang, & Buchner, 2007). The sample size for this population in the health program has to be a good size and well rounded. I want to achieve good data and realistic sample size. The response rate I anticipate from this population is to be 70%. The reading level needs to be around .07-.08 for literature purposes and reliability for each participant in the health program (Faul, Erdfelder, Buchner, & Lang, 2009). To collect data for this survey I will use paper and pencils for the
If the p-value is less than the significance level (α) of 0.05 (5%) the null hypothesis will be rejected. The power is 1-β, 1 - 0.20 = 0.80 (the probability of detecting differences between the groups). Reasonable numbers for power are between 0.7 and 0.9 (Sharp et. al, 2009).
Testing a pain reliever using 20 people to determine if it is effective. The random variable represents the number of people who find the pain reliever to be effective.
Applying the Kantian theory to this situation, should Dr.L tell Bruce that he is receiving the placebo? First, Kant does not seem to approve of human research. One would argue that in research patients will always be a means to an end. The patients are subjected to conditions that do not guarantee benefit and the end result will always benefit the researchers or the general population regardless
What do you guys think about the question posed on page 257, "What about using placebos in studies of serious illnesses like depression? Treatments for it are known to be effective, though imperfect. There is little doubt that the most powerful way to show a drug's efficacy and safety is to assign patients at random to the drug or a placebo. But depressed patient who get a placebo may not improve; they may get worse and even become suicidal" (257-258). This is a sticky situation, but I believe that placebos should still continued to be given. The patient's are aware of the consequences and the fact that they may receive a placebo. Being apart of the study, given the medicine or placebo, will help the research in anyway. Resources should be
When designing a study, researchers need to “power” it, which means determine how many people they need to enroll in their study to prove what they want to prove.
As a group we formulated a procedure in which we would attack the study in order to get the most accurate and precise data possible. The group set a table in the Atrium at a time in which we could all meet from 2:15 to 3:30. It was also a time in which the atrium would have enough people getting food to procure a diverse crowd in which to gather data from. We wanted to get as close to an equal amount of male and female participants as possible. We ended up with 16 males and 14 females. On the table were thirty of each type of soda was laid out in small dixie cups behind a note card labeled with its corresponding letter. The letter indicated which soda it contained. We then had Logan Hatchel be the designated person who would know what each cup of each letter contained in the event that it needed to be refilled. We did this to maintain the state of the study of being double-blind to ensure that we would not influence the results by accidently leaking and or influencing the participants study by knowing the contents of each soda. We also bought a case of water which was then poured out into cups. This
In an experiment involving pain symptoms, a placebo is giving to control group A and the actual pain pill is being giving to control group B. In every experiment involving placebo it uses either the single-blinded method or double-blinded. In this experiment we are only using the single-blinded method and this is where only the experimenter knows which patient or control group is receiving a placebo. In some experiments they use the double-blinded method to make sure neither the patient or the control group know that they are receiving a placebo. The reason they do the double-blind method is because when the patient asks the experimenter if she or he is receiving the placebo neither will actually
During this experiment, a person would ring in acting like they were a doctor and would instruct the nurse to administer a 20mg drug called “Astroten” to a patient which was fictional, the drug was a dud. The “Doctor” would they say he/she would give the signature of approval later to give the drug to the patient. The bottle named “Astroten” was placed in the cabinet ready for the nurse to find but the label would clearly state that 10mg is a maximum dose.
In this experiment, the participants are classified into two groups, one with less than 20 push-ups (n=37) and the other with 20 or more push-ups
A hospital is conducting a double blind test of a new depression drug. The test is expected to take into consideration 20 doctors and about 400 patients to be tested. It is planned that half of the patients will get the new drug and half will get traditional Prozac and neither the doctors nor the patients will know who is getting which drug and at what time. The test is organized such that only two test supervisors will have access to the entire program and possibly know who is getting what.
The participant, along with the accomplices, were asked to look at the lines in the flash cards (there were two flash cards in each set, the first one containing one vertical line and the second one containing the choices; three vertical lines varying with different lengths to which they will match the line in the first flash card with) and were asked as to which letter the line on the first flash card corresponds with the second flash card. The answers in this line task are obvious and the accomplices and the experimenter had agreed on what they would answer on each trial before the start of the experiment. There were 18 sets or trials and the accomplices gave the wrong answer 12 times. They were asked to tell their answers out loud and the real participant was seated at the end of the row, hence, they were the last to give their answers. There was also a control group that only had a real participant alone, no
In this fictional school district, 28500 students did not have the disease, but only 27960 will test negative. 99.89% of the negative test results are correct because 27930 out of 27960 is 99.89%. These are called the true negatives, which is a test result that is one that does not detect the condition when the condition is absent. The table also shows the false positives, which is a test result which incorrectly indicates that a particular condition or attribute is present. In this case, the false positives would be that 1500 students out of 30000 students, 2040 students will test positive. So in this case about 26.47% of the positive results is incorrect, which is not accurate at all!