please note that the data im about to fill in is stats data which needs computer (R statistics) i know it will take long to complete this question but please help me. the end is the question. below is the data you will be using to answer

,"x" 1,5 2,5 3,5 4,5 5,5 6,5 7,5 8,5 9,5 10,5 11,5 12,5 13,5 14,501.137507609365 15,501.895642760055 16,502.906535993968 17,504.039907591815 18,505.669590352571 19,508.089499414666 20,508.851274941065 21,508.495906365299 22,509.284317152793 23,511.858663500052

24,511.883881561311 25,509.95933979685 26,512.441529585577 27,513.689284854783 28,514.642326471966 29,516.586844523863 30,519.02690411417 31,522.078090063428 32,520.428545024173 33,517.743274341295 34,519.237366869451 35,523.618342966524 36,524.680308269378 37,524.853193518559 38,529.102666812718 39,529.634980536099 40,530.639656226783 41,532.427095751681 42,533.436454003455 43,535.113852373059 44,533.25219089014 45,531.407602353742 46,534.897280561786 47,539.848101608776 48,541.058409756433 49,542.718800200945 50,547.478642033076 51,548.122359514088 52,549.420698253348 53,548.428940649274 54,545.968535586259 55,547.122822356245 56,547.015847773642 57,546.744222223373 58,551.76648721617 59,556.588400416318 60,557.213680210273 61,559.749118334316 62,565.528326727378 63,566.3601879779 64,568.733795717576 65,567.570068998056 66,563.568059104866 67,565.375171362113 68,565.30323787098 69,563.933162100375 70,569.486347578283 71,575.263964842965 72,577.738744426981 73,581.603001617974 74,588.272078631757

75,590.302556248671 76,593.795234748713 77,594.317218078885 78,592.332166271256 79,594.284324335579 80,592.747712512923 81,590.205637462681 82,595.581656868947 83,599.42781216111 84,601.562784203563 85,606.833326154176 86,614.970630016507 87,617.969720311589 88,620.210700791094 89,620.600021606969 90,619.829975450558 91,622.12614956787 92,622.035096711515 93,621.422865083191 94,626.392262506493 95,627.700289021709 96,629.765847322911 97,635.548932661705

98,643.625568854416 99,648.432600042966 100,650.506097927561 101,651.622794906493 102,651.997693861372 103,655.562484381545 104,658.089885320966 105,659.082215425847 106,662.774982627625 107,661.259971604863 108,661.720825598971 109,666.658914779702 110,674.399883572119 111,678.475307537062 112,680.26287775964 113,682.75754970146 114,684.293727049372 115,687.137712556511 116,689.352680506575 117,691.411262589267 118,693.224811502393 119,688.366174131608 120,686.264946144382 121,690.095749269552 122,697.366254563777 123,699.58416816301 124,702.008099600284 125,706.003297254351

126,709.386678814961 127,712.125523977112 128,713.935464341206 129,716.759374723955 130,717.455189505276 131,711.927817427334 132,709.597444053564 133,713.673368462731 134,722.365848393678 135,724.122431274804 136,727.233664821554 137,733.34549940093 138,737.676110161544 139,740.42936734487 140,742.827198283234 141,746.848524545526 142,746.498783255575 143,740.794960482232 144,739.763890178565 145,742.325344990586 146,751.411874658422

147,752.032141168459 148,753.280728117651 149,759.287886463327 150,763.053916157186 151,765.610846783056 152,768.344866242347 153,771.833756944596 154,770.400123969866 155,764.432519355952 156,762.97494662085 157,763.588201492999 158,773.045144585752 159,770.981076259892 160,768.15610222933 161,773.671694164084 162,777.490195091262 163,779.574838208633 164,782.182737985501 165,784.780326019957 166,781.477508026742 167,774.373287270373 168,772.823213227409 169,773.273356085721 170,782.67614159094 171,778.426086700694 172,773.294815269685 173,778.747076977033 174,782.738237137813

175,786.50056795964 176,790.846444084144 177,792.907277210948 178,788.089574838141 179,779.111689544257 180,777.153199875989 181,778.716265294474 182,788.274293564008 183,783.613241342934 184,779.561825454303 185,789.666604928187 186,794.512196524708 187,796.640125436676 188,802.075577791059 189,803.083781027367 190,795.188480860979 191,783.620626004336 192,779.971655361753 193,783.47137594753 194,793.941784315714

195,789.564649691466 196,787.302553039724 197,800.725550370343 198,806.583967392639 199,807.928373308962 200,814.534035813576 201,813.859064885406 202,804.905919168611 203,794.532426148443 204,792.603333607803 205,796.26407995786 206,805.93504897017 207,800.427814268749 208,798.501834326295 209,812.585399425279 210,818.396860303057 211,819.42221009245 212,825.93416330827 213,825.674121321659 214,817.289956181745 215,807.85640054808 216,805.445696930825 217,805.810217991626 218,815.132652783967 219,810.049839672051 220,806.453825513131 221,816.878113906029

222,820.77747599612 223,819.345350678411 224,821.406143753734 225,821.505179880869 226,814.64686641821 227,806.39096265546 228,804.312890342666 229,803.3754554431 230,812.409100636893 231,807.915506260128 232,804.463675529783 233,814.408926798969 234,817.243403295443 235,813.20218669224 236,813.055764694249 237,811.22582323383 238,802.452955323941 239,793.047331961815 240,790.138621549803

• Visually describe the sales and any inherent patterns
• Use time series methods and R to infer from dataset: Arima, sarima, ARCH and GARCH methods an other innovations?
• Select the best model and use it to predict sales.
• Draw conclusions from analysis.