problem 1: describe the main components of a deterministic time series. How far are such methods effective in forecasting?
problem 2:
a) Describe the concept of conditional probability. How is it associated to Baye’s theorem?
b) Prove that for any two events A and B, we have P (AB) ≤ P (A+B) ≤ P (A) + P (B), where P (A) and P (B) are probabilities of occurrence of events A and B.
problem 3: What is meant by the term standard error? Describe with the help of an illustration how standard error can be found out.
problem 4: A sample of 400 students in a class is found to have a mean height of 171.38 cms. If mean height of the population is known to be 171.17 cms with a standard deviation of 3.30 cms, will it be regarded that there is no significant difference between the sample and the population mean heights?
problem 5: Fit a straight line to the given data. Compare the estimated values with the actual values.
problem 6: State the steps you will follow while designing a problemnaire. Make a small problemnaire for collecting data associated to consumption and income of households.
problem 7: Distinguish between the given:
a) Type I and Type II errors
b) Parameter and statistic
c) Point estimate and interval estimate
problem 8: prepare short notes on the given terms:
a) Systematic sampling.
b) Confidence interval.