work part d

part a

The business problem facing the director of broadcasting operations for a television station was the issue of standby hours (ie hours in which unionized graphic artists at the station are paid but are not actually involved in any activity) and what factors were related to standby hours. A study of standby hours was conducted for 26 weeks. The variables in the study are described below and the data from the study are shown in the accompanying table. Complete parts a through e below Standby hours (Y)---Total number of standby hours in a week Total staff present (X1) ---Weekly total of people-days Remote hours (xy) -- Number of hours worked by employees off-site Click the icon to view the data table PLEASE RUN SPSS TO OBTAIN THE REQUIRED DATA TO ANSWER THE QUESTIONS BELOW a. State the multiple regression equation Y = - 331.5+ (18)X +(-0.1)X (Round to one decimal place as needed) The business problem facing the director of broadcasting operations for a television station was the issue of standby hours (.e. hours in which unionized graphic artists at the station are paid but are not actually involved in any activity) and what factors were related to standby hours. A study of standby hours was conducted for 26 weeks. The variables in the study are described below and the data from the study are shown in the accompanying table Complete parts a through e below Standby hours (Y)-Total number of standby hours in a week Total staff present (X)-Weekly total of people-days Remote hours (X2) --Number of hours worked by employees off-site Click the icon to view the data table. PLEASE RUN SPSS TO OBTAIN THE REQUIRED DATA TO ANSWER THE QUESTIONS BELOW! d. Predict the mean standby hours for a week in which the total staff present have 310 people-days and the remote hours are 400, There would be 160.59 standby hours predicted for the week. Round to two decimal places as needed.) var4 var5 Standby_Hours Total_Staff_Pre Remote_Hours 247 338 414 177 333 600 270 358 656 211 372 631 196 341 528 135 289 399 195 334 382 118 293 399 116 325 343 147 311 338 154 304 353 146 312 289 115 283 388 161 307 402 274 322 151 245 335 228 201 350 271 183 339 440 237 327 475 175 328 347 319 449 188 325 336 188 322 267 197 317 235 261 315 164 232 33 270 152 The problem facing a manager is to assess the impact of factors on full-time (FT) job growth. Specifically, the manager is interest in the impact of total worldwide revenues and full-time voluntary tumover on the number of full-time jobs added in a year. Data were collected from a sample of 20 "best companies to work for." The data includes the total number of full-time jobs added in the past year, total worldwide revenue (in Smilions), and the full-time voluntary turnover (%). Use the accompanying data to complete parts (a) through (d) below. Click the icon to view the data table. YOU WILL HAVE TO RUN SPSS TO OBTAIN THE NECESSARY DATA TO ANSWER THE QUESTIONS BELOWI a. State the multiple regression equation Let X, represent the Total Worldwide Revenues (Smilions) and lot Xz represent the FT Voluntary Tumover (%) Y -- 174,3403 + (0.0333) X, (40.8332) X2 (Round the constant and Xy-coefficient to the nearest integer as needed. Round the Xy-coefficient to four decimal places as needed.) Row 1 var 2 3 4 5 6 7 8 9 10 11 12 Total FT Jobs A Total Worldwid FT Voluntary T -67 3691.728 12.764 87 290.401 4.559 59 1498.124 2.784 1264 3050.195 16.188 110 11682.636 4.677 -128 1931 7.853 2673 31300 12.632 360 1543 8.582 2035 74000 8.281 314 3319 18.283 124 396.196 10.076 254 5040 6.496 -237 5955.676 4.285 1264 12316.379 20.038 523 2470.72 6.471 -19 686 9.721 486 12151.797 8.87 237 1556 3.402 -72 871.8 15.677 1085 15000 3.287 13 14 15 16 7 a un 8 9 0 1 2