For problems 1 through 6, you are given a response set of numbers and a #*predictor set of numbers. For each one, plot the points, create a linear #*model, state the prediction formula, and predict the given value IN R STUDIO #* #* 1) Here are the values: xvals.1 <- c(18, 22, 17, 38, 3, 47, 20, 21, 15, 10, 22, 27, 23, 9, 26, 40, 26, 7, 22, 13) yvals.1 <- c( 33, 4, 14, 6, 25, 45, 36, 39, 8, 42, 25, 11, 42, 1, 9, 47, 37, 3, 30, 32)

#* predict the response when the predictor is 32

#* 2) Here are the values: xvals.2 <- c(7, 26, 0, 22, 42, 34, 33, 15, 14, 1, 3, 19, 20, 17, 41, 33, 42, 22, 30, 41, 44, 40, 19, 18, 29, 19, 8, 36, 18, 40, 31, 16, 31, 35, 48, 18, 47, 24, 21, 5, 41, 41, 41, 24, 30, 30, 6, 16, 34, 19) yvals.2 <- c(67, 126, -19, 174, 187, 196, 232, 190, 173, -10, 72, 88, 119, 34, 270, 268, 357, 92, 180, 258, 260, 174, 104, 57, 174, 47, -20, 243, 198, 236, 224, 147, 258, 267, 394, 83, 283, 228, 69, 40, 331, 174, 210, 83, 288, 166, -8, 68, 232, 54) #* predict the response when the predictor is 24 #* 3) Here are the values: xvals.3 <- c(9, 5, 10, 5, 5, 1, 1) yvals.3 <- c(514, 40, 1031, 32, 35, 1, 7) #* predict the response when the predictor is 4 #* 4) Here are the values: xvals.4 <- c(8, 3, 11, 10, 3, 1, 6) yvals.4 <- c(43, 51, 36, 44, 87, 15, 38) #* predict the response when the predictor is 12 #* 5) Here are the values: xvals.5 <- c(32, 3, 5, 16, 31, 14, 9, 18, 19, 7, 13, 11) yvals.5 <- c(151, 30, -14, 146, 189, 159, -7, 178, 74, 68, 4, 14) #* predict the response when the predictor is 10 #* 6) Here are the values: xvals.6 <- c(0, 11, 24, 14, 30, 17, 2, 23, 2, 29, 25, 8) yvals.6 <- c(3, -12, 183, 176, 155, 164, -37, 101, 44, 187, 180, 151) #* predict the response when the predictor is 17