SSolve clearly

You are interested in analyzing the effects of Pokemon on traffic accidents. To do so, you collected data on the amount of Pokemon (measured in Pokes) per driver and the number of accidents registered during the day. The table below shows an extract of your data: Driver Pokes accidents John 3.02 5 Jacob 2.15 2 Jingleheimerschmidt 0.09 a, What type of dataset is this? Use OLS and the sample statistics provided below to estimate the parameters of the simple linear regression model shown below (round to two decimals): accidents, = Bo + B, Pokes, + uh b. Bo = C. B1 Sample Statistics average traffic accidents per day = accidents = 7.5 average Pokes per driver = Pokes = 0.25 sample traffic accident variance - incidents = 25 sample Pokes variance = pokes = 0.3 sample covariance between traffic accidents and Pokes = 0.75 d. What is the expected number of accidents on a day with 0.5 Pokes of Pokemon? Round to two decimals. e. Calculate the R-squared for this regression, Round to two decimals.You are interested in analyzing the effects of Pokemon on traffic accidents. To do so, you collected data on the amount of Pokemon (measured in Pokes) per driver and the number of accidents registered during the day. The table below shows an extract of your data: Driver Pokes accidents John 3.02 5 Jacob 2.15 2 Jingleheimerschmidt 0.09 a, What type of dataset is this? Use OLS and the sample statistics provided below to estimate the parameters of the simple linear regression model shown below (round to two decimals): accidents, = Bo + B, Pokes, + uh b. Bo = C. B1 Sample Statistics average traffic accidents per day = accidents = 7.5 average Pokes per driver = Pokes = 0.25 sample traffic accident variance - incidents = 25 sample Pokes variance = pokes = 0.3 sample covariance between traffic accidents and Pokes = 0.75 d. What is the expected number of accidents on a day with 0.5 Pokes of Pokemon? Round to two decimals. e. Calculate the R-squared for this regression, Round to two decimals