"When you interview for a position as a statistician, you can expect to be asked about your knowledge of statistics, analytical and critical thinking skills, and your ability to draw conclusions from gathered data. Prepare to answer situational questions that may require you to analyze a set of data and explain its meaning or design an experiment to gather important statistical data. Your employer will want to make sure you can use your theoretical knowledge of statistics to solve hands-on, real world problems."
It was about the Simpson paradox. Consider the GPA for female and male students in 2 different years. If the mean GPA for the male students is higher in both years, it is possible that when we consider both years together then the mean GPA will be higher for the female group?
Ask me a weird question, "what is the weakness of logistic regression?" I did not know it. So I answered frankly, "sir, I do not know this question. Can you suggest a book, or a paper about it so that I can learn it?" He refused to answer and finished the interview. Later I asked several professors in department. One professor said "I guess he means the logistic regression does not work well if the data contains too many zeros (something like perfect separation)". Well, if this is the answer, is it the weakness of logistic regression, or the flaw of dataset itself? I think It is not a weakness of a statistical method, it is that we fit a wrong model.
How to deal with missing value for categorical variable?
Is this position going to be satisfying for you?
Why did you applied this position?
how you handle conflicts
If you are trying to estimate the parameter p of the binomial distribution B(n,p) from data where the number of successes is 0, what is the confidence interval for the p estimate
Why drives you to work at Paraxel?
Describe your related experience in the past (internship, course projects, etc.)
What are type 1 and 2 errors?
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