d. StatCrunch gives the following linear regression output for this data: Simple linear regression results: Number of Named Storms = -464.77855 + 0.24055944 Year HESY Sample size: 12 R-sq = 0.48946637 Interpret the values of the slope and y-intercept for this model. Make sure to include units for the slope. woled nevis el s16b ard to 101q191 1602 A d e. Use the model to predict the number of named storms for 2020. f. In fact, NOAA has reported that we ended the 2020 hurricane season with 30 named storms. Did our model predict this? Calculate the residual. Is it positive or negative? g. BONUS: Interpret the value of the coefficient of determination (R-sq).7. 2020 was a very active year for named Atlantic storms. The following table of data was retrieved from the National Oceanic and Atmospheric Administration website. It gives the number of named Atlantic storms for every 5th year beginning in 1960. Year Number 7 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 6 10 9 11 11 14 19 15 28 19 11 a. Identify the predictor and response variables. b. A scatterplot of the data is given below: in 3 10 and Number of Named Storms 25+ , independent or normal boris 20 nozser shophurt OSOS ard behrs ew words bohogey end AAON Joint Hypolil sis Tests ( dependent sample formal population int sample 1960 1970 1980 1990 2000 2010 Year Describe the direction of the scatterplot and any potential outliers. c. StatCrunch computes the correlation coefficient as r = 0.699619. How would you characterize the strength of the linear association between year and number of named storms