Q. 14 Distinguish between non-randomised and randomised test.
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- In her book Red Ink Behaviors, Jean Hollands reports on the assessment of leading Silicon Valley companies regarding a manager's lost time due to inappropriate behavior of employees. Consider the following independent random variables. The first variable x1 measures manager's hours per week lost due to hot tempers, flaming e-mails, and general unproductive tensions. I need help with sketching, (d) and (e)Using the information in the diagram below, was intention-to-treat (ITT) analysis done? Randomized (n = 123) Allocated to intervention Allocated to standard care (GI + HT + standard care) Discontinued Discontinued intervention study (n = 6) (n = 15) Analyzed (n = 68) Analyzed (n = 55) No, because there are participants that discontinued the study in both groups Yes, because all study participants were analyzed in the groups they were allocated to No, because the number of participants in the intervention and control groups are unequal OYes, because drop-out rates were similar in both intervention and control groupsWhat is the degree of freedom for one sample T test with n=15?
- Suppose that you want to perform a hypothesis test to compare several population means, using independent samples. In each case, decide whether you would use the one-way ANOVA test, the Kruskal–Wallis test, or neither of these tests. Preliminary data analyses of the samples suggest that the distributions of the variable are not normal but have the same shape.A.) What is the sample mean difference in inflammation between no massage and massage? sample mean difference=?(exact number) B.)We want to test to see if the population mean difference is greater than zero, meaning muscle with no treatment has more inflammation than muscle that has been massaged.State the null and alternative hypothesis Ho= Ha= C.)Use StatKey or other technology to find the P-value from a randomization distribution.P-value=?Round your answer to three decimal places.1. True or False? A Kruskal-Wallis test is used to compare a continuous outcome in more than two independent samples.
- You wish to test the following claim (H.) at a significance level of a = 0.05. Н.: и — 72.5 Ha:u + 72.5 а You believe the population is normally distributed, but you do not know the standard deviation. You obtain a sample of size n = 14 with mean M = 81.7 and a standard deviation of SD = 15.6. What is the test statistic for this sample? (Report answer accurate to three decimal places.) test statistic = What is the p-value for this sample? (Report answer accurate to four decimal places.) p-value %|Give me an example problem regarding the topic of Confidence interval for Means - Unknown Variance, Large Sample with complete solution.Suppose that you've collected gpa data for a simple random sample (SRS) of Business majors (Group 1), Fine Arts majors (Group 2) and English majors (Group 3) at UD. Assume that the Single-Factor ANOVA test rejected the null hypothesis that the mean gpa for all three groups was the same value. If you followed up this hypothesis test with a 95% Confidence Interval estimate of the value of mu subscript 1 minus mu subscript 2, the difference between the population mean gpa of Business majors and Fine Arts majors at UD, and the CI turned out to be given by open parentheses negative 0.527 comma space 0.915 close parentheses, INTERPRET this CI. That is, explain specifically how this CI allows you to compare the mean gpas of Business majors and Fine Arts majors at UD. Are they significantly different, or not. EXPLAIN!
- 2. A partially completed ANOVA table for a completely randomized design is shown here: Source SS df | MS F Treatments 18.4 6 Error Total 45.2 41 a) Complete the ANOVA table. b) How many treatments are involved in the experiment? c) Do the data provide sufficient evidence to indicate a difference among the population means? Test, using a = 0.10. d) Find the approximate p-value for the test in part c).A Levene's test is significant at p-value < 0.05. Which can we conclude? O The variances are not equal. An assumption was violated O The variances are equal. An assumption was violated The variances are not equal. An assumption was not violated O The variances are equal. An assumption was not violatedHmm.132.
