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The time is limited and the questions vast. But I will try to write as many ECOM20001 assignment 3 answers as possible in this blog post. Here we go.
This question for 8 marks is not an easy target. You are required to create a variable in R Studio. Before you are creating a variable for the assignment, it is important that you know what variable you are dealing with.
In R Studio, you can create a re-coding variable or a renaming variable. Seeing the needs of the question, I propose to go with the renaming variable in ECOM20001 assignment 3 answers.
Then, you need to run 4 regressions in the tool where the question has defined which variable to be dependent and which to be constant. You have to run 4 different regressions, that means you have to run a linear regression.
For writing the ECOM20001 assignment 3 answers to question 2, you need to know how to use a ggplot2 command in R. I will give you a brief for that.
Under ggplot(df), you will define what dataset to use. The question says it should be log_birthweight and nprevisit. Since you have to create a scatter plot, your ggplot2 layer or geom will be point type defined as geom_point.
For a clear ECOM20001 assignment 3 answers plot, you should label the axes and redefine the legend that you are using. This is achieved through a labs command.
For example, you want X axis to show nprevisit and Y to show log_birthweight. Then your command becomes labs(title=“Question2”, x=“nprevisit”, y=“log_birthweight”)
The ECOM20001 assignment 3 answers for the third question will be based on a new variable creation. This new variable will be the square of the previous one. The name is the same but the function has now changed.
Now, the new variable nprevisit_sq is defined as nprevisit_sq X nprevisit_sq. Based on this, you have to run a regression where the dependent variable is log_birthweight and the constants are various. Thus, this regression will be multiple regression.
For adding a multiple regressions in ECOM20001 assignment 3 answers, you can use the lm() function where you add the dependent variable and the independent variable till all of them are accounted for. For example, lm(log_birthweight ~ smoker + alcohol + drinks + gambles + nprevisit + nprevisit_sq + tripre1 + tripre2 + tripre3 + unmarried + educ + age, DATAVAR)
In the ECOM20001 assignment 3 answers for this question, you have to consider that the confidence interval is 95% and all the variables from the above regression are fixed. Then, make a change in nprevisit from 2 to 4. record the changes.
Then make a change in nprevisit from 12 to 14. Again, record the changes.
Now you have to explain why there was a significant difference in these two changes even though the variable was changed by only 2. For that, you have to analyse the regression results from the first change and the second change, apply the concepts of multiple linear regressions and then state your understanding using the secondary literature over why the change is significant for both cases.
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