problem 1: describe the main components of a deterministic time series. How far are such methods effective in forecasting?
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.