D different categories of the independent variable result in diferent probabilit
ID: 3269246 • Letter: D
Question
D different categories of the independent variable result in diferent probabilities of be longing to a category in the dependent variable 13. When analyzing a causal relationship where the independent variable is numerical and the dependent variable is numerical, we can conclude that the variables are causally related if A numerical changes in the independent variable result in numerical changes to the de- pendent variable B a change in numerical value in the independent variable results in different probabilities of belonging to a category in the dependent variable C differ ent categories of the independent variable result in having different numerical values in the dependent variable D different categories of the independent variable result in different probabilities of be 14. When analyzing a causal relationship where the independent variable is numerical and the A numerical changes in the independent variable resalt in numerical changes to the de- B a change in numerical value in the independent variable results in different probabilities longing to a category in the dependent variable variable is categorical, we can conclude that the variables are causaly related if C different categories of the independent variable result in having different numerical values D different categories of the independent variable result in different probabilities of be 15. An economist would like to determine if household size has a causal effect on household pendent variable of belonging to a category in the dependent variable in the dependent variable longing to a category in the dependent variable income. The economist gathers data for both of these variables. Housebold size is defined as the total number of individuals living at a single address. Housebold incomme is defined with an ability to earn in the household. The economist Observes that the incomes of all homes vary greatly, with a standard deviation of The economist splits the income data into 6 groups (the maximum household size studied is 6) The standard deviation of income with a household of size i is about The standard deviation of income with a household of size 2 is about $20,000. The as the total sum of income of all individuals about $20,000. $20,000. standard deviation of all other sized houses also From this, the economist can conclude that was about the same variation in the data. A household size and housebold income are causally related B household size and household income are not causally related C household size and household income are causally related for some household sizes D the causal test is inconclusive 16. A significance level is A the probability that a confidence interval does NOT contain the population parameter. B the probability that a confidence interval does contain the population parameter. C the probability that a confidence interval does NOT contain the sample statistic D the probability that a confidence interval does contain the sample statistic 17. A confidence level is A the probability that a confidence interval does NOT contain the popalation parameter. B the probability that a confidence interval does contain the populstion parameter C the probability that a confidence interval does NOT contain the sample statistic D the probability that a confidence interval does contain the sample statistic.Explanation / Answer
As per forum rules answering 1 question per post:
13) A is right option
The questions mentions the following:
The independent variables and the dependent variables, both are numerical. Meaning none of the variables are categorical. A numerical change in the independent variables leads to numerical change in the dependent variable. Hence, option A is right as it mentions both variables as numerical.
B mentions dependent variables as categorical , hence is wrong.
C mentions independent variables as categorical , hence is wrong.
D mentions independent and dependent variables as categorical , hence is wrong.
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