Suppose that you want to estimate the relationship between people's weight (W) and the number of times they eat out in a month (EO): Upper W Subscript i equals beta 0 plus beta 1 EO Subscript i plus u Subscript i, where beta 0 is the intercept of the population regression line; beta 1 is the slope of the population regression line; u Subscript i is the error term; and the subscript i runs over observations, iequals1, ... , n. For this, you collect data from a random sample of 300 people. After analyzing the data, you determine that the covariance between people's weight and the number of times they eat out in a month is 4.94 and the variance of the number of times people eat out in a month is 4.04. You also find that the mean weight of people in the sample is 63.82 kg and the mean number of times people eat out in a month is 2.46. The OLS estimator of the slope beta 1 is nothing. (Round your answer to two decimal places.)