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## Week 4 Electronic Text Assignment (Custom from teacher)

by: smartwriter Notetaker

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# Week 4 Electronic Text Assignment (Custom from teacher)

Marketplace > Week 4 Electronic Text Assignment Custom from teacher
smartwriter Notetaker
CSU - Dominguez hills
GPA 3.0

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Week 4 Electronic Text Assignment (Custom from teacher)
COURSE
PROF.
No professor available
TYPE
Study Guide
PAGES
6
WORDS
KARMA
50 ?

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This 6 page Study Guide was uploaded by smartwriter Notetaker on Monday November 16, 2015. The Study Guide belongs to a course at a university taught by a professor in Fall. Since its upload, it has received 31 views.

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Date Created: 11/16/15
Week 4 E-Text Problem 1: Sixty­four students in an introductory college economics class were asked how many credits  they had earned in college, and how certain they were about their choice of major. Research  question: At α = .01, is the degree of certainty independent of credits earned? Data to construct  the contingency table are below 0­9 Credits Earned Very Uncertain: 12 Somewhat Certain: 8 Very Certain: 3 10­59 Credits Earned Very Uncertain: 8 Somewhat Certain: 4 Very Certain: 10 50 or More Credits Earned Very Uncertain: 1 Somewhat Certain: 11 Very Certain: 7 Chi­square Contingency Table Test for Independence    Col 1   Col 2   Col 3   Total   Row Observed  12   8   1   21   1 Expected   7.55   7.22   6.23   21.00   O ­ E   4.45   0.78   ­5.23   0.00      (O ­ E)² /  2.63   0.08   4.39   7.11   E   Row Observed  8   4   11   23   2 Expected   8.27   7.91   6.83   23.00   O ­ E   ­0.27   ­3.91   4.17   0.00   (O ­ E)² /  0.01   1.93   2.55   4.49   E   Row Observed  20   3   10   7   3 Expected   7.19   6.88   5.94   20.00   O ­ E   ­4.19   3.13   1.06   0.00   (O ­ E)² /  2.44   1.42   0.19   4.05   E   Tota Observed  23   22   19   64   l Expected   23.00   22.00   19.00   64.00   O ­ E   0.00   0.00   0.00   0.00   (O ­ E)² /  5.08   3.43   7.13   15.64   E   15.64 chi­ square 4 df .0035 p­value Test figure = 15.64 P­value = 0.0035 which is below our alpha of 0.01 therefore we turn down the null theory and  state that there is a variation in the sum of credits earned and the assurance of selecting a major. Problem 2: A student team examined parked cars in four different suburban shopping malls. One hundred  vehicles were examined in each location. Research question: At α = .05, does vehicle type vary  by mall location? (Data are from a project by MBA students Steve Bennett, Alicia Morais, Steve  Olson, and Greg Corda.) Data to construct the contingency table are below Car Minivan Somerset: 63 Somerset: 21 Oakland: 49 Oakland: 15 Great Lakes: 44 Great Lakes: 18 Jamestown: 46 Jamestown: 13 Full­sized Van SUV Somerset: 2 Somerset: 27 Oakland: 3 Oakland: 19 Great Lakes: 3 Great Lakes: 26 Jamestown: 2 Jamestown: 12 Truck Somerset: 14  Oakland: 6 Great Lakes: 17 Jamestown: 9 Chi­square Contingency Table Test for Independence    Somerset Oakland       Great Lakes     Jamestown     Total   Car Observed   63   49   44   46   202   Expected   62.72   45.44   53.34   40.50   202.00   O ­ E   0.28   3.56   ­9.34   5.50   0.00      (O ­ E)² / E   0.00   0.28   1.64   0.75   2.66   Minivan Observed   21   15   18   13   67   Expected   20.80   15.07   17.69   13.43   67.00   O ­ E   0.20   ­0.07   0.31   ­0.43   0.00   (O ­ E)² / E   0.00   0.00   0.01   0.01   0.02   Full­sized Van Observed   2   3   3   2   10   Expected   3.11   2.25   2.64   2.00   10.00   O ­ E   ­1.11   0.75   0.36   0.00   0.00   (O ­ E)² / E   0.39   0.25   0.05   0.00   0.69   SUV Observed   27   19   26   12   84   Expected   26.08   18.89   22.18   16.84   84.00   O ­ E   0.92   0.11   3.82   ­4.84   0.00   (O ­ E)² / E   0.03   0.00   0.66   1.39   2.08   Truck Observed   14   6   17   9   46   Expected   14.28   10.35   12.15   9.22   46.00   O ­ E   ­0.28   ­4.35   4.85   ­0.22   0.00   (O ­ E)² / E   0.01   1.83   1.94   0.01   3.78   Total Observed   127   92   108   82   409   Expected   127.00   92.00   108.00   82.00   409.00   O ­ E   0.00   0.00   0.00   0.00   0.00   (O ­ E)² / E   0.43   2.36   4.29   2.16   9.24   9.24 chi­square 12 df .6827 p­value P­value = 0.6827 which is not below our alpha of 0.05 therefore we accept the null theory and  state that there is not a variation in car types found at every mall. Problem 3: High levels of cockpit noise in an aircraft can damage the hearing of pilots who are exposed to  this hazard for many hours. A Boeing 727 co­pilot collected 61 noise observations using a  handheld sound meter. Noise level is defined as “Low” (under 88 decibels), “Medium” (88 to 91  decibels), or “High” (92 decibels or more). There are three flight phases (Climb, Cruise,  Descent). Research question: At α = .05, is the cockpit noise level independent of flight phase?  (Data are from Capt. Robert E. Hartl, retired.) Data to construct the contingency table are below Low Noise Level Medium Noise Level High Noise Level Climb: 6 Climb: 18 Climb: 1 Cruise: 6 Cruise: 8 Cruise: 13 Descent: 2 Descent: 3 Descent: 14 Chi­square Contingency Table Test for Independence    Climb Cruise     Descent Total   Low Observed   6   6   2   14   Expected   4.93   5.32   3.75   14.00 O ­ E   1.07   0.68   ­1.75   0.00      (O ­ E)² / E   0.23   0.09   0.81   1.13   Medium Observed   18   8   3   29   Expected   10.21 11.03   7.76   29.00 O ­ E   7.79   ­3.03   ­4.76   0.00   (O ­ E)² / E   5.94   0.83   2.92   9.69   High Observed   1   13   14   28   Expected   9.86   10.65   7.49   28.00 O ­ E   ­8.86   2.35   6.51   0.00   (O ­ E)² / E   7.96   0.52   5.65   14.13 Total Observed   25   27   19   71   Expected   25.00 27.00   19.00   71.00 O ­ E   0.00   0.00   0.00   0.00   (O ­ E)² / E   14.13 1.44   9.39   24.96 24.96 chi­square 4 df .0001 p­value P­value = 0.0001 which is below our alpha of 0.05 therefore we turn down the null theory and  state that there is freedom between groups, particularly, the intensity of noise does vary by the  part of the flight. Problem 4: Can people really identify their favorite brand of cola? Volunteers tasted Coca­Cola Classic,  Pepsi, Diet Coke, and Diet Pepsi, with the results shown below. Research question: At α = .05,  is the correctness of the prediction different for the two types of cola drinkers? Could you  identify your favorite brand in this kind of test?  Since it is a 2 x 2 table, try also a two­tailed two­sample z test for π1 = π2 (see Chapter 10) and  verify that z2 is the same as your chi­square statistic.Which test do you prefer? Why? (Data are  from Consumer Reports 56, no. 8 [August 1991], p. 519.) Data to construct the contingency  table are below Yes, got it right No, got it wrong Regular Cola: 7 Regular Cola: 12 Diet Cola: 20 Diet Cola: 7 Chi­square Contingency Table Test for Independence    Regular Diet     Total Total   Yes Observed   7   20   14   41   Expected   8.47   12.03   20.50 41.00   O ­ E   ­1.47   7.97   ­6.50 0.00      (O ­ E)² / E   0.25   5.28   2.06   7.59   No Observed   12   7   32   51   Expected   10.53   14.97   25.50 51.00   O ­ E   1.47   ­7.97   6.50   0.00   (O ­ E)² / E   0.20   4.24   1.66   6.10   Total Observed   19   27   46   92   Expected   19.00   27.00   46.00 92.00   O ­ E   0.00   0.00   0.00   0.00   (O ­ E)² / E   0.00   0.00   0.00   0.00   Total Observed   38   54   92   184   Expected   38.00   54.00   92.00 184.00   O ­ E   0.00   0.00   0.00   0.00   (O ­ E)² / E   0.46   9.52   3.72   13.69   13.69 chi­square 4 df .0083 p­value Hypothesis test for two independent proportions p1 p2 p c 0.3684 0.7407  p (as  0.587 decimal)  p (as    7/19   20/27 27/46 fraction) 7. 20. 27.  X 19 27 46  n ­0.3723  difference 0.  hypothesized difference 0.1474  std. error ­2.53  z .0116  p­value (two­tailed) P­value = 0.0083 which is less than our alpha of 0.05 so we can turn down the null theory. There  is enough proof for us to state there is freedom between groups, particularly; the diverse right  assumptions are not more than what we would anticipate from possibility alone. P­value =0.0116, which is less than out alpha of 0.05 so we turn down the null theory. Therefore  once more, not sufficient proof with this sample size that correct assumptions between diet and  regular are better than possibility only. I favor using the z­test on the variation in ratios, as the calculation is a bit straighter forward.  Both tests have restrictions for small samples.

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