STATISTICS

ANOVA, ANCOVA, REGRESSION, RSTUDIO

Directions: Answer the following questions inside the picture and choose the correct answer. Explain why it is the correct answer. All the details for the question is indicated in the picture for each number.

1.

A researcher wishes to see if the total number of infections that occurred in three groups of randomly selected hospitals is the same. The data are shown in the table. Group A Group B Group C 557 476 105 315 232 110 920 80 167 178 116 155 At a = 0.05, is there enough evidence to reject the claim that the number of infections in the three groups of hospitals is the same? a. Since the computed value of 5.346 is less than the tabulated value of 5.991, there is no enough evidence to reject the claim that there is no difference in the number of infections in the groups of hospitals. b. Since the computed value of 5.991 is greater than the tabulated value of 5.346, there is enough evidence to reject the claim that there is no difference in the number of infections in the groups of hospitals. c. Since the computed value of 5.346 is less than the tabulated value of 5.991, there is enough evidence to reject the claim that there is no difference in the number of infections in the groups of hospitals. d. Since the computed value of 5.991 is less than the tabulated value of 5.346, there is no enough evidence to reject the claim that there is no difference in the number of infections in the groups of hospitals.Suppose that we want to build a model that predicts the group membership of a hurricane, either tropical (0) or non-tropical (1) based on the latitude of formation of the hurricane. The response variable is the binary variable Type. new (type of hurricane) and the predictor variable is FirstLat (First Latitude). Using R, we build a model by applying the gim () function. For the logistic regression model, we specify family = "binomial". The data is available at https://userpage.fu-berlin.de/soga/200/2010 data sets/hurricanes.xlax . The R code is iget up filename my . filename 0.05 implying that the distribution of the data is significantly different from the normal distribution. b. The p-value > 0.05 implying that the distribution of the data is significantly different from the non-normal distribution. c. The p-value > 0.05 implying that the distribution of the data is not significantly different from the normal distribution. d. The p-value >0.05 implying that the distribution of the data is not significantly different from the non-normal distribution