For two way ANOVA model, a significant interaction effect implies that both predictors(factors) have an effect on the average response value Select one: a. False b. True
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For two way ANOVA model, a significant interaction effect implies that both predictors(factors) have an effect on the average response value
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- Studies indicate that excessive noise at night can affect weight gain. One study of n = 127 rats compared the weight gain of rats exposed to excessive noise at night and the weight gain of rats in a quiet night environment. Sample statistics for the study are given in the table below. Use this information to determine if there is significant evidence that weight gain of rats exposed to excessive noise at night is different on average than weight gain of rats in a quiet night environment. Excessive noise at night environment (Group 1) Quiet night environment (Group 2) Sample mean (grams) 22.4 19.9 Sample standard deviation (grams) 6.4 3.8 Observations/Sample size 69 58 Is this a one-tailed or a two-tailed test? Explain in one or two sentences.what does it means that the variable are positively correlated?The multivariate analysis considers more than one factor of independent variables that influence the variability of dependent variables. a. True b. False
- Researchers investigate how the presence of cell phones influence the quality of human interaction. Subjects are randomly selected from a population and divided into an experimental group that is asked to leave their phones in the front of the room and a control group that are not asked to leave their cell phones at the front of the room. Subjects are left alone for 10 minutes and then asked to take a survey designed to measure quality of interactions they had with others in the experiment. What statistical test is appropriate?A significant interaction was found between depression, social support and GPA. These results should be considered with caution and further research should be done to better understand the relationships between these variables. Furthermore, those working with college students should consider the overall well-being of the student, as it is possible that their academic performance may not be affected by anxiety and/or depression. IS THIS A TYPE 1 ERROR OR A TYPE 2 ERROR IN RESEARCH?Dr. Mackintosh believes a new olfactory therapy would be more successful in promoting weight loss among obese patients. His patients are first weighed and then randomly assigned to olfactory therapy, dance therapy, or a control condition. At the end of the three weeks, the amount of weight lost is recorded. The results indicate no significant difference in the amount of weight lost between the three conditions. Identify the independent variable along with each level and the dependent variable.
- The director of student services at Oxnard College is interested in whether women are just as likely to attend orientation as men before they begin their coursework. A random sample of freshmen at Oxnard College were asked what their gender is and whether they attended orientation. The results of the survey are shown below: Data for Gender vs. Orientation Attendance Women Men Yes 440 410 No 238 239 What can be conduded at the a - 0.10 level of significance? For this study, we should use z-test for a population proportion a. The null and alternative hypotheses would be: Ho: Select an answer v Select an answer v Select an answer v (please enter a decimal and note that p1 and ul represent the proportion and mean women and and u2 represent proportion and mean for men.) H: Select an answer v Select an answer v Select an answer v (Please enter a decimal) b. The test statistic ? v (please show your answer to 3 decimal places.) c. The p-value = (Please show your answer to 4 decimal places.) d.…Twenty samples of students from the first year were taken for the study related to fitness level in a university. The researcher has collected the data for a few variables: gender and fitness test score. Fitness Camp No Gender Fitness score Fitness score (Before Attend camp) (After Attend camp) 1 M 444 526 2 F 780 862 3 F 475 557 4 F 490 572 5 M 755 837 6. M 766 848 7 F 540 622 8 M 623 705 9. F 600 682 10 620 702 11 505 590 12 M 640 725 13 F 523 608 14 F 700 785 15 M 710 795 16 M 726 811 17 M 740 825 18 F 550 635 19 F 685 770 20 F 460 545 Range of Fitness Score: 0 to 900 1. Determine whether this set of data is sample or population? Why? Which formulae to be used when calculating the standard deviation of fitness score before and after camp 2. Calculate the standard deviation for fitness score before and after students attended the fitness camp for the whole samples using the formula in (1) 3. Based on the sample standard deviation in part (2), explain whether the fitness camp can…Peter Boag, studied the inheritance of beak depth in Galapagos finches by looking at the relationship between parent beak depth (in mm) and that of their offspring. He collected two sets of parent offspring data, once in 1976 and again in 1978. For both years he followed birds to determine which pairs belonged to which nests. Most of the parents had been previously captured so their beak depths were known. He then captured the offspring when they fledged and measured their beak depth. He calculated the "midparent" beak depth (the average beak depth of the two parents) and then compared that to beak depth of their offspring. Use regression analysis to estimate heritability for the trait beak depth from the Galapagos finches data in the above table.
- They then decided to determine whether the effect of the phone depended on how dependent people were on their phones. They had participants complete a scale to measure phone dependence (e.g., I would have trouble getting through a normal day without my phone) and classified them as high or low in dependence. They then analysed working memory task performance in a 2 (location: outside, desk) x 2(dependence: high, low) ANOVA. In this design, "dependence" is a(n) O a. Independent variable O b. Extraneous variable O c. Dependent variable O d. Subject variableA researcher conducts a two-way ANOVA to determine how eating breakfast affects children's grades in school. Factor A has three levels: no breakfast, sugary breakfast, high protein breakfast. Factor B has two levels: males and females. Factor B has no main effect and there is no interaction effect. It is safe to conclude that _________. a. Factor A does not influence the participant's grades b. Factor B does not influence the participant's grades c. Factor A has an influence on the participant's grades d. Factor B has an influence on the participant's grades Clear my choiceRead 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 affect 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 - affect 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…
