You are concerned that nausea may be a side effect of Tamiflu, but you cannot just give Tamiflu to patients with the flu and say that nausea is a side effect if people become nauseous. This is because nausea is common for people who have the flu. From past studies you know that about 34% of people who get the flu experience nausea. You collected data on 1926 patients who were taking Tamiflu to relieve symtoms of the flu, and found that 711 experienced nausea. Use a 0.01 significance level to test the claim that the percentage of people who take Tamiflu for the relief of flu symtoms and experience nausea is greater than 34%.

We are testing whether a particular program of low impact exercise can improve the cholesterol level of stroke patients. We enroll a group of stroke patients in our study, and after six weeks we measure their serum cholesterol level in mmol/L, resulting in the following data:  6.1 9.3 6.3 4 9 5.5 6.3 4.2 4.7 7.8 4.3 7.5 9.1 4.2 6.9 8.1 5.6 9.4 8.3 8.8 7.2 5.7 6.5 3.8 3.8 9 9.4 4.5 8 7 4.5 9.4 6.6 4.1 6.6 9.1 3.9 5.3 (a) Construct a 95% confidence interval. _______< u < ______ From an existing study, we know that the average cholesterol level of all stroke patients is 7 mmol/L. We want to know if the level in our patients is significantly different from this. (b) What is our Test statistic? ______ (c) What is the two-tailed p-value of this result? ______

Question 7: A research team is interested in the effect of Parent-Child Interaction Therapy (PCIT) in reducing children’s disruptive behaviors for children with disruptive behavior disorders (DBD). The research team recruited 12 families with a child with DBD and interviewed the parents about the number of disruptive behaviors the child has at home. After three weeks' therapy, the research interviewed again about the child's disruptive behaviors.   The disruptive before and after the therapy is list below. Test the researcher’s hypothesis at a 0.05 significant level. List 4 steps.   Family Disruptive behaviors before PCIT Disruptive behaviors after PCIT 1 3 2 2 4 4 3 5 3 4 5 3 5 6 5 6 5 3 7 5 5 8 7 6 9 8 5 10 5 2 11 3 2 12 3 4

If you have a research scenario in which the IV has three or more levels and is between subjects in nature with a quantitative DV, then you would use the One Way Between Subjects ANOVA. O True O False

The well-known psychologist Dr. Elbod has established what he calls his Generalized Anxiety Scale (GAS). The GAS, which is a scale from 0 to 10, measures the "general anxiety" of an individual, with higher GAS scores corresponding to more anxiety. (Dr. Elbod's assessment of anxiety is based on a variety of measurements, both physiological and psychological.) We're interested in making predictions about individuals' sleep behavior based on their GAS scores. The bivariate data below give the GAS score (denoted by x) and the number of hours of sleep last night (denoted by y) for each of the fifteen adults participating in a study. A scatter plot of the data is shown in Figure 1. Also given is the product of the GAS score and the sleep time for each of the fifteen adults. (These products, written in the column labelled "xy", may aid in calculations.) GAS score, x 00 2.1 3.6 8.0 3.8 7.0 9.1 5.0 5.9 9.1 1.5 6.5 4.0 3.0 8.0 Sleep time, y (in hours) 8.2 7.4 1.0 Send data to calculator 7.4 8.4…

Question 9 Dr. Jameson wanted to know if IQ scores differed between male and female participants in his study. He gave 28 participants an IQ test and then compared IQ scores for gender differences. He hypothesized that there would be a statistically significant gender difference in IQ scores. Contrary to Dr. Jameson's hypothesis, there were no differences in IQ scores between men and women in his study. From the results of the study, Dr. Jameson must the research hypothesis. the null hypothesis and fail to reject; reject reject; retest reject; fail to reject retest; reject

A researcher wants to know if a treatment significantly changes the wellbeing of someone with depression. The average person with depression scores a 7.2 on a wellbeing scale with a SD of 1.4 points. The researcher administers the treatment to 25 clients for a month and finds their wellbeing at the end to be 7.7. Assume an alpha level of .05.  Imagine we know that a treatment actually does have an effect but the researcher concludes there is no effect. 1a. What error has the researcher made?  1b. Why might a researcher make this error?  1c. What is the probability of this error?  1d. How could we decrease this probability?

Help me please

Step 1 A major health study indicated that there's a birth month effect for schizophrenia. If a child is born during a certain month, he or she has a significantly higher chance of developing schizophrenia later in life, however, the chance of developing schizophrenia only increases by 1 in 10 million. Step 2 Based on what you know about t-tests, how can there be a significant difference for that particular month when there's such a small increase in the chances of developing schizophrenia?

A hypothetical study looks at the effect of drinking alcohol on health. Across all genders and age groups, people who do not drink tend to be healthier on average than people who do drink. However, people who drink regularly are on average healthier than those people who have recently stopped drinking. Is it reasonable to conclude that for the sake of health, we should not start drinking, but if we have already started drinking alcohol, it is healthier to continue and not to stop?