3.Using the iris dataset:
a) combine the Setosa and Versicolor into group \u201c0\u201d and label the Virginica to \u201c1\u201d. Create a new variable called iris$Group with the 0 or 1 labels, \u00a0\u00a0 <\/p>\n
b) build a logistic regression model using any available data that will predict the observation being Virginica ( value of 1 in Group variable),
c) calculate the probability of a new plant being a Virginica for the following parameters:\u00a0 <\/p>\n
Sepal.Width =5 Petal.Length =10 Petal.Width =7 Sepal.Length=9\u00a0 <\/p>\n
4.Using the kyphosis dataset:
a) convert the kyphosis$Kyphosis variable to numeric, assign a 1 to present and a 0 to absent,
b) build a logistic regression using all other variables and estimate the probability of the observation having a \u201cpresent\u201d hyphosis. What can you say about the coefficients? Are the significant?
c) calculate the probability of kyphosis being \u201cpresent\u201d for the following observation: Age=50, Start=10, Number=5.\u00a0 <\/p>\n
5. Using all the single variable regressions from Exercise 1, test if the variable pairs are homoscedastic or heteroscedastic. Plot your findings. Using the plot(x=my_x_variable, y=my_y_variable, type=\u201dp\u201d) function. Use my_data$variable_name to define x and y variables in the function.\u00a0 <\/p>\n","protected":false},"excerpt":{"rendered":"
3.Using the iris dataset: a) combine the Setosa and Versicolor into group \u201c0\u201d and label the Virginica to \u201c1\u201d. Create a new variable called iris$Group with the 0 or 1 labels, \u00a0\u00a0 b) build a logistic regression model using any available data that will predict the observation being Virginica ( value of 1 in Group […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[17],"class_list":["post-70053","post","type-post","status-publish","format-standard","hentry","category-research-paper-writing","tag-political-science"],"_links":{"self":[{"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/posts\/70053","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/comments?post=70053"}],"version-history":[{"count":0,"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/posts\/70053\/revisions"}],"wp:attachment":[{"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/media?parent=70053"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/categories?post=70053"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/tags?post=70053"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}