Recent research indicates that the effectiveness of antidepressant medication is directly related to the severity of the depression (Khan, Brodhead, Kolts & Brown, 2005).  Based on pretreatment depression scores, patients were divided into four groups based on their level of depression.  After receiving the antidepressant medication, depression scores were measured again and the amount of improvement was recorded for each patient. The following data are similar to the results of the study. Low Moderate High Moderate Moderately Severe   Severe 0.3 1.2 2.2 1.8 3.8 1.7 1.4 2.8 3.2 0.4 0.6 2.6 2.3 1.2 1.6 2.6 2 3.2 1.6 2.2 0.6 1.2 1.6 1 2.7 1 2.2 0.6 1.4 1.6 3.3 2.7 2.2 2.9 3.7 2.6 0.9 0.7 3.4 3.1 2.6 1.7 0.8 1.8 2 1.4 1.6 4.1 1.7 0.9 3.3 2.3 1.6 1.1 3.5 1.4 3.5 1.9 0.4 4.2 1.5 2.3 2.2 2.9 1.4 2.2 2.7 2.8 2.1 1.9 1.9 3.9 1.5 2.7 0.8 1.5 1 3 2.1 3.7 1.5 0.9 2.4 1.9 2.7 3.2 0.8 2.7 2.2 2.9 1.8 1.2 2.4 1.7 3.2 1.3 2.2 2.4 1.1 1 2.6 2 2.4 3.8 0.9 1.3 1.8 1.9 1.7 1.7 1.2 3.8 1.3 0 3.3 3 1.9 2.5 1.1 1.8 0 3.6 1.8 2.9 2.1 3.2 2.9 2.8 3.2 1.8 0.8 2.3 1 3 4.4 2.2 1.8 0.2 2.3 2.3 1.8 4.1 3.6 2.2 1.5 2 2.2 1.9 3.1 2.6 2.7 2.8 2.1 1.3 1.1 2.5 0.7 1.5 0.8 4 0.7 2.6 2.1 3 1.9 1.3 1.7 3.3 3.2 0.9 1.4 2.4 4 0 4 2.2 1.8 1.6 2.8 3.2 2.8 2 0.6 1.3 1.9 2.4 0.6 2.3 1 2.4 1.8 2.4 3.1 0.9 1.8 3.9 This is the summary table for the ANOVA test:   S.S. d.f. M.S. Between 12.783010204082 3 4.2610034013606 Within 168.27714285714 192 0.87644345238095 TOTAL 181.06015306122 195 From this table, you obtain the necessary statistics for the ANOVA: F-ratio:  4.8616980248812 p-value:  0.00278 η2= 0.070600902451238 What is your final conclusion?  Use a significance level of α=0.02. These data do not provide evidence of a difference between the treatments There is a significant difference between treatments   Explain what this tells us about the equality of means.

The DASS-21 questionnaire is a validated measure of depression, anxiety, and stress. For the general population, the mean for anxiety is µ = 4.2. Anxiety levels are calculated based on self-reported answers to questions on a scale from 0 through 42, with lower scores indicating lower anxiety.   Participants with gastrointestinal issues (specifically inflammatory bowel disease, IBD) completed the DASS-21. Use the data presented below to determine whether having gastrointestinal issues like IBD significantly increases risk for anxiety. Test whether or not the performance of this sample is significantly higher than the normal population using the proper t-test.  Here are the data:   Anxiety scores: 12, 15, 10, 8, 10, 5, 10, 13, 4, 6   ANALYSES AND UNGRADED OPTIONAL GUIDING QUESTIONS: 1a. Identify the Indep.Variable:__                  Dep.Variable:__ Is it the Hypothesis one-tailed or two-tailed?__ Proper t-test statistic:__ Why? _ State Hypotheses mathematically: H0:__ H1:__  State…

Social functioning is the ability for an individual to interact or adapt in a normal or usual way in social environments. Albert et al. (2007) asked if relatives of patients with OCD are as healthy as those in general healthy populations. They measured the social functioning of relatives using a 36-item survey with scores ranging from 0 (worst possible health) to 100 (best possible health). The mean score for the general healthy population was 77.43. Using the sample data, test whether there was a difference. Scores: 20, 60, 48, 92, 50, 82, 48, 90, 30, 68, 43, 54, 60, 62, 94, 67, 63, 85 State hypotheses     2. Set the criteria using α= 0.05     3. Calculate t     4. What should you conclude?

Read through this scenario and look at the data that was collected.  State the null and all possible research hypotheses.  Review the results below (I used SPSS) and answer the questions that follow. Scenario:  A researcher wants to see if gender and / or income affects the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help.  The independent variables are gender, income, and the interaction of gender and income.  The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affects the total amount of help offered.  Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA.  His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect.  The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables…