For a simple linear regression modely=β0+β1x+εy = \beta_0 + \beta_1 x + \varepsilony=β0​+β1​x+ε,consider the following statements where β^0\hat{\beta}_0β^​0​ and β^1\hat{\beta}_1β^​1​ are estimates of β0\beta_0β0​ and β1\beta_1β1​:

Discuss the impact of Information Technology in the Industrial Revolution of India.

Question Let XXX be a Poisson variate with parameter λ\lambdaλ such that P(X = 2) = 2P(X = 4) + 20P(X = 6) What is the coefficient of skewness? Options: (a) 1/√3(b) 1(c) 1/2(d) −1/√3

Question:Which of the following statements are associated with residuals of a regression model? The sum of the residuals in any regression model that contains an intercept is always zero. The sum of the observed values yiy_iyi​ is not equal to the sum of the fitted values y^i\hat{y}_iy^​i​. The sum of the residuals weighted by the corresponding regressor variable is zero. The sum of the residuals weighted by the corresponding fitted values is zero. Select the c

Indian Statistical Service (ISS) examination conducted by UPSC is one of the most prestigious career opportunities for statistics graduates in India. Every year, many talented students from B.Sc. Statistics, M.Sc. Statistics, Mathematics, and related fields appear for this examination with the dream of becoming government statisticians.

What Is Non-Probability Sampling? Non-probability sampling refers to sampling techniques where not every member of the population has a known or equal chance of being selected. Unlike probability sampling, which relies on random selection, non-probability methods depend on the researcher's judgment or convenience. Common types of non-probability sampling include: Convenience Sampling : Selecting participants who are easiest to reach. Judgmental or Purposive Sampling : Choosin