You are analyzing a dataset with 749 datapoints. You decide to create a linear regression model with this dataset, using 12 predictor variables. Using this information, what is the degrees of freedom associated with the sum of squares regression in your analysis?
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- how do the four assumptions underlying the GLM impact the data analysis process ?The report “airline Quality rating 2016” (www.airlinequalityrating.com/reports/2016_aQr_Final.pdf,retrieved april 22, 2017) included the accompanying data onthe on-time arrival percentage and the number of complaintsfiles per 100,000 passengers for U.S. airlines.The report did not include data on the number of complaintsfor two of the airlines. Use the given data from the otherairlines to fit the least squares regression line and use it topredict the number of complaints per 100,000 passengersfor Spirit and for Virgin America.A sociologist recorded the number of contacts entered in a cell phone and the number of texts sent in a week for 20 cell phone users. The resulting data were used to conduct a hypothesis test to investigate whether there is a linear relationship between the number of contacts and the number of texts sent. What are the correct hypotheses for the test?
- At the 5% significance level, are the predictor variables jointly significant? At the 5% significance level, evaluate each of the independent or predictor variables. Think about the five common problems with regression models, what is most likely wrong with this model?When conducting a retrospective cohort study what are some possible selection and information bias one can encounter especially because we have to use existing data? how can they be avoided or minimized (mitigated) during the study study design to avoid them?The dataset below was collected from a survey to determine whether CFT development in the island can be used as a strategy for the sustainable management and utilization of the fishery and aquatic resources in small islands. It shows the monthly income (in thousand pesos) estimated by 200 randomly selected fishers in Guimaras according to the type of fishers (i.e., the income source of fishers is solely fishing or they have alternative/supplemental livelihood such as island hopping services, sari-sari store ownership, fish value adding and/or vending, souvenir selling, carpentry, as construction worker, farming and tour guiding) and their perceived benefit from CFT development in the island. From this dataset and using = 0.05, is there a significant difference in estimated monthly income due tofisher type? How about due to the CFT perceived benefit? How about due to the interaction between fishertype and the perceived CFT benefit?a. Analyze manually and assume that the…
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- The director of an obesity clinic in a large northwestern city believes that drinking soft drinks contribute to obesity in children. To determine whether a relationship exists between these two variables, she conducts the following pilot study. Eight- 12-year-old male volunteers are randomly selected from children attending a local junior high school. Parents of the children are asked to monitor the number of soft drinks consumed by their child over a one week period. The children are weighed at the end of the week and their weights converted into body mass index (BMI) values. The BMI is a common index used to measure obesity and takes into account both height and weight. An individual is considered obese if they have a BMI value 30. The following data or collected: child. # of soft drinks consumed BMI 1 3 20 2 1 18 3…Consider the outcome of serum concentration vitamin D and the predictor cardiorespiratory fitness. Provide a definition of confounding variables in the context of this study, and provide some examples of potential confounders.When we use a least-squares line to predict y values for x values beyond the range of x values found in the data, are we extrapolating or interpolating? Are there any concerns about such predictions?