It has been suggusted that the highest priority of retirees is travel. Thus, a study was conducted to investigate the differences in the length of stay of a trip for pre- and post-retirees. A sample of 714 travelers were asked how long they stayed on a typical trip. The observed results of the study are found below. You may round all answers for this problem to the nearest hundredth. Number of Nights Pre-retirement Post-retirement Total 4-7 248 173 421 8-13 79 75 154 14-21 36 52 88 22 or more 11 40 51 Total 374 340 714 To import data to R, copy and paste the R codes below number=c(rep("4-7",421),rep("8-13",154), rep("14-21",88), rep("22_or_more",51)) retirement=c(rep("pre-retirement",248),rep("post-retirement", 173),rep("pre-retirement",79), rep("post-retirement",75), rep("pre-retirement",36), rep("post- retirement",52),rep("pre-retirement", 11), rep("post-retirement",40)) data-data.frame(number, retirement) table(data) With this information, construct a table of estimated expected values. Use two digits after the decimal. Number of Nights Pre-retirement Post-retirement 4-7 8-13 14-21 22 or more Now, with that information, determine whether the length of stay is independent of retirement using a = = 0.01. (a) x²= =0 Use as many digits after the decimal as possible. (b) Find the degrees of freedom: 3 (c) The final conclusion is A. There is not sufficient evidence to reject the null hypothesis that the length of stay is independent of retirement. B. We can reject the null hypothesis that the length of stay is independent of retirement and accept the alternative hypothesis that the two are dependent.

College Algebra (MindTap Course List)

12th Edition

ISBN:9781305652231

Author:R. David Gustafson, Jeff Hughes

Publisher:R. David Gustafson, Jeff Hughes

Chapter4: Polynomial And Rational Functions

Section4.6: Rational Functions

Problem 11SC: Find the mean hourly cost when the cell phone described above is used for 240 minutes.

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I need help on filling out this following table for statistics. Please help me find the chi squared value as well

It has been suggusted that the highest priority of retirees is travel. Thus, a study was conducted to investigate the differences in the length of stay of a trip for pre- and post-retirees. A sample of 714 travelers were asked how long they stayed on a typical trip. The observed results of the study are found below. You may round all answers for this problem to the nearest hundredth.

To import data to R, copy and paste the R codes below number=c(rep("4-7",421),rep("8-13",154),rep("14-21",88),rep("22_or_more",51)) retirement=c(rep("pre-retirement",248),rep("post-retirement",173),rep("pre-retirement",79),rep("post-retirement",75),rep("pre-retirement",36),rep("post- retirement",52),rep("pre-retirement",11),rep("post-retirement",40)) data=data.frame(number,retirement) table(data) With this information, construct a table of estimated expected values. Use two digits after the decimal. Now, with that information, determine whether the length of stay is independent of retirement using alpha=0.01. (a) chi^(2)= Use as many digits after the decimal as possible. (b) Find the degrees of freedom: 3 (c) The final conclusion is A. There is not sufficient evidence to reject the null hypothesis that the length of stay is independent of retirement. B. We can reject the null hypothesis that the length of stay is independent of retirement and accept the alternative hypothesis that the two are dependent. number=c(rep("4-7",421),rep("8-13",154),rep("14-21",88),rep("22_or_more",51)) retirement=c(rep("pre-retirement",248),rep("post-retirement",173),rep("pre-retirement",79),rep("post-retirement",75),rep("pre-retirement",36),rep("post-retirement",52),rep("pre-retirement",11),rep("post-retirement",40)) data=data.frame(number,retirement) table(data)