A mobile manufacturing company distributed a newly launched mobile to 100 retail stores. These stores also sell another famous brand of mobile having same features. The manager of the company wants to compare the popularity of the newly launched mobile (say, Brand A) with the other popular mobile (say, Brand B). For this purpose, she selects a sample of 100 stores and noted the total number of sold mobiles of each brand. The data are recorded in the following table:
| Store No. | Brand A | Brand B | Store No. | Brand A | Brand B | |
| 1 | 204 | 462 | 51 | 521 | 239 | |
| 2 | 328 | 454 | 52 | 327 | 284 | |
| 3 | 262 | 211 | 53 | 531 | 225 | |
| 4 | 364 | 284 | 54 | 490 | 175 | |
| 5 | 478 | 168 | 55 | 427 | 365 | |
| 6 | 368 | 304 | 56 | 310 | 384 | |
| 7 | 506 | 162 | 57 | 433 | 182 | |
| 8 | 362 | 328 | 58 | 313 | 505 | |
| 9 | 151 | 484 | 59 | 424 | 270 | |
| 10 | 371 | 256 | 60 | 295 | 183 | |
| 11 | 522 | 159 | 61 | 288 | 463 | |
| 12 | 328 | 362 | 62 | 239 | 517 | |
| 13 | 532 | 178 | 63 | 244 | 435 | |
| 14 | 491 | 230 | 64 | 270 | 495 | |
| 15 | 428 | 392 | 65 | 224 | 449 | |
| 16 | 311 | 322 | 66 | 484 | 440 | |
| 17 | 434 | 349 | 67 | 173 | 418 | |
| 18 | 314 | 339 | 68 | 256 | 498 | |
| 19 | 425 | 312 | 69 | 416 | 410 | |
| 20 | 296 | 446 | 70 | 233 | 546 | |
| 21 | 289 | 352 | 71 | 323 | 409 | |
| 22 | 240 | 467 | 72 | 279 | 529 | |
| 23 | 245 | 392 | 73 | 340 | 214 | |
| 24 | 271 | 293 | 74 | 464 | 262 | |
| 25 | 225 | 500 | 75 | 383 | 216 | |
| 26 | 485 | 239 | 76 | 423 | 461 | |
| 27 | 174 | 283 | 77 | 351 | 497 | |
| 28 | 257 | 380 | 78 | 404 | 271 | |
| 29 | 417 | 295 | 79 | 226 | 475 | |
| 30 | 234 | 466 | 80 | 164 | 511 | |
| 31 | 324 | 365 | 81 | 205 | 274 | |
| 32 | 280 | 449 | 82 | 329 | 295 | |
| 33 | 341 | 189 | 83 | 263 | 326 | |
| 34 | 465 | 218 | 84 | 365 | 157 | |
| 35 | 384 | 530 | 85 | 479 | 368 | |
| 36 | 424 | 321 | 86 | 369 | 256 | |
| 37 | 352 | 485 | 87 | 507 | 272 | |
| 38 | 405 | 369 | 88 | 363 | 226 | |
| 39 | 227 | 457 | 89 | 163 | 334 | |
| 40 | 165 | 420 | 90 | 372 | 218 | |
| 41 | 203 | 293 | 91 | 523 | 184 | |
| 42 | 327 | 315 | 92 | 329 | 437 | |
| 43 | 261 | 399 | 93 | 533 | 206 | |
| 44 | 363 | 409 | 94 | 492 | 177 | |
| 45 | 477 | 213 | 95 | 429 | 173 | |
| 46 | 367 | 256 | 96 | 177 | 502 | |
| 47 | 505 | 190 | 97 | 435 | 406 | |
| 48 | 361 | 238 | 98 | 315 | 358 | |
| 49 | 161 | 495 | 99 | 426 | 381 | |
| 50 | 370 | 428 | 100 | 297 | 408 | |
Answer the following:
i) Which mobile brand has more average sales?
ii) Which mobile brand shows greater variability in the sales?
iii) Compute the skewness and kurtosis for the given data and interpret the results.
iv) Determine the correlation between both mobiles.
v) Compute suitable width of the class intervals for both brands,
vi) Construct the continuous frequency distribution for both brands.
vii)Represent the raw data as well as grouped data using suitable diagram/graph.
We can solve this step by step manually, using the data you provided. Since it’s a large dataset (100 stores), we will outline the numerical procedure and calculate key statistics systematically. --- ### Step i) Which mobile brand has more average sales? The average sales (mean) is: $$ \bar{X} = \frac{\text{Sum of all sales}}{n} $$ #### Sum of sales: Let’s denote: * Brand A sales = $X_A$ * Brand B sales = $X_B$ * $n = 100$ From the data (summing carefully in batches of 10 to avoid errors): * Brand A sum: 1–10: $204+328+262+364+478+368+506+362+151+371 = 3,394$ 11–20: $522+328+532+491+428+311+434+314+425+296 = 4,081$ 21–30: $289+240+245+271+225+485+174+257+417+234 = 2,837$ 31–40: $324+280+341+465+384+424+352+405+227+165 = 3,367$ 41–50: $203+327+261+363+477+367+505+361+161+370 _______ ____ _________ _______ ___ _________ _________ _________ _______ _______ _________ __________.
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