[3 pts] 4. Consider the following scenarios. Decide whether a Type I or Type II error is occurring and identify the type of bias that may have contributed to the error. Each type of bias will only be used once: availability bias, confirmation bias, historical bias, selection bias, survivorship bias. a. Researchers are studying the effectiveness of a new biopesticide on crop yields, and the team strongly believes that it will increase crop yields. The researchers conduct a one-sided test and conclude that the biopesticide does not significantly affect crop yields, despite several farmers in tropical climates reporting decreased yields while using the biopesticide. ☐ Type I ☐ Type II Type of bias: b. In a test to determine whether a vaccine was causing blood clots, the sample did not include additional potential causative factors correlated with the patient's risk of developing blood clots. The analysis found the vaccine caused blood clots. Type I Type II Type of bias: C. A consulting firm is evaluating the effectiveness of flood resilience strategies in a local business district. One year after a major flooding event, they survey the remaining businesses that are operating in the district. The firm concludes that the flood resilience strategies are effective, noting that all the operating businesses did not experience major flood damage and have remained open. ☐ Type I Type II Type of bias: 2

Does the test result Provide sufficient evidence that light alcohol consumption has a negative impact on the driving performance of a sleep deprived driver. Why or why not

A science project involves testing the effects of different types of music on plant growth.  A sample of 24 newly sprouted bean plants is obtained.  The plants are randomly assigned to each experimental condition (6 per group). The experimental conditions are:  rock music, heavy metal, country, and classical.  The dependent variable is the height of each plant after 2 weeks.    The ANOVA results are summarized as follows: MSB = 10 and SSW =40. Construct a summary table for this study

One year at a university, the algebra course director decided to experiment with a new teaching method that might reduce variability in final-exam scores by eliminating lower scores. The director randomly divided the algebra students who were registered for class at 9:40 A.M. into two groups. One of the groups, called the control group, was taught the usual algebra course; the other group, called the experimental group, was taught by the new teaching method. Both classes covered the same material, took the same unit quizzes, and took the same final exam at the same time. The final-exam scores (out of 40 possible) for the two groups are shown in the accompanying table. Find a 99% confidence interval for the ratio of the population standard deviations of final-exam scores for students taught by the conventional method and for students taught by the new method. Assume that both populations are normally distributed. (Note: s₁ = 6.613, $₂ = 5.762, and for df = (19,40), F0.005 = 2.63.) Click…

It has been hypothesized that allergies result from a lack of early childhood exposure to antigens. If this hypothesis were true, then we would expect allergies to be more common in very hygienic households with low levels of bacteria and other infectious agents. To test this theory, researchers at the University of Colorado sampled the houses of 61 children 9-24 months old and recorded two variables: (1) whether the child tested positive for allergies and (2) the concentration of bacterial endotoxin in the house dust (endotoxin units per ml, EU/ml)1. The following are the endotoxin levels at the homes of the 51 children tested negative for allergies.  708.23  911.60  976.81  1316.63  262.74  9772.08  370.76  229.16  2570.51891.19  3163.20  1777.65  1288.57  436.23  2631.63  1173.52  911.67  7942.42  740.32  356.92  1175.48  1480.55  2754.61  575.62  573.89  468.26 1000.71  364.22  1025.26  1022.04  645.41  363.57  977.47  1022.75  1860.63 371.13  174.73  399.68  1479.77  2882.96…

A 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 choice