Consider the following causal diagram:
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- What do you mean by Simultaneous Causality? Explain in detail.If two variables, x and y, have a very strong linear relationship, then: There might not be any causal relationship between x and y There is evidence that y causes a change in x There is evidence that x causes a change in y O None of these alternatives is correct.To that end let X and Y to be two variables and suppose we have collected data on both of them from an underlying population: X1. X2......Xn V₁, V2, ... Yn Two-way table can be constructed in three different cases. Obs Gender 1 2 3 4 EX: We have collected data on Salary, Education, Gender, and Working Hours from all 10 employees. of a Tech company in Kabul. Education Salary 5 6 7 8 9 10 M M F F F M M M M M HS BA PowerPoint Slide Show- (BivarPart1.pptx)]-PowerPoint Bivariate Analysis: Two way Table Two way Table: 3: Working hrs and Salary: MA MA PHD MA BA BA HS BA 10 20 30 35 50 38 25 23 15 26 Working Hrs 6 8 9 9 10 9 8 7 6 7 Whr8 Total Sal 20 2 0 0 2 [20-30) 0 4 0 4 Sal> 30 0 0 4 4 Total 2 4 4 10 Fr(Whr =30)= 4 MULTIPLE CHOICE QUESTION 0 Rewatch Submit
- Which of the scatter diagrams below suggests a strong positive linear relationship between the x and y variables?a.State the predictors available in this model.You hypothesize that there may be a non-linear relationship between your predictors, where there may be more mosquitoes in sites with water and with caribou hosts. How do you create your model? Assume that "caribou" corresponds to the presence/absence of caribou Assume that "water" corresponds to the presence/absence of water number of mosquitoes ~ caribou * water number of mosquitoes ~ caribou + water presence/absence of mosquitoes ~ caribou + water presence/absence of mosquitoes ~ caribou * water
- To that end let X and Y to be two variables and suppose we have collected data on both of them. from an underlying population: x1,x2,..., Xn V₁, V2, Yn Two-way table can be constructed in three different cases. Obs Gender 1 M M EX: We have collected data on Salary, Education, Gender, and Working Hours from all 10 employees of a Tech company in Kabul. Education Salary HS 10 BA 20 30 26 35 50 38 25 23 15 26 2 3 4 5 6 7 8 9 10 F E F PowerPoint Slide Show - (BivarPart1.pptx) - PowerPoint F M M M M M Bivariate Analysis: Two way Table Two way Table: 1: Gender and Education: HS BA 0 4 4 MA M MA PHD MA BA BA HS BA Working Hrs 6 8 9 9 10 9 8 7 6 7 F 0 M2 2 2: Education and Salary: Sal 30 Total 0 2 0 4 3 3 1 4 Total 3 7 10 1 10 Fr(Education=PHD, SalaryCat in [20,30))=? 1 MULTIPLE CHOICE QUESTION 0 Rewatch SubmitExercise 2. Marginal and Conditional Relationships can be Very Different. For 100 mild cases of eczema, a new treatment had a higher cure rate than the old treatment (33.3% of 90 vs. 20% of 10). For 100 severe cases of eczema, again the new treatment had a higher cure rate than the old treatment (60% of 20 vs. 50% of 80). Over all 200 eczema cases, however, the old treatment had a higher cure rate than the new treatment- i.e. Simpson's Paradox strikes again. (a) Compute the overall cure rates for the new and old treatments. (b) Which treatment, old or new, would you choose and why?Consider the following simple linear regression. iid Y = Po + B₁X + e, e~ N(0,02), i 1,..., n.
- 3. If two variables, x and y, have a strong linear relationship, then y causes x to happen b. x causes y to happen there may or may not be any causal relationship between x and y d. а. с. None of these alternatives is correct.If two variables, x and y, have a strong linear relationship, then ______. Select one: A. None of the answers is correct B. x causes y to happen C. y causes x to happen D. there may or may not be any causal relationship between x and yHaving a brother increases one's monthly earnings by $200." Why is this an example of an incomplete causal statement?
