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The PLANTS2 data file gives data on four different species of plants grown in a

ID: 3202629 • Letter: T

Question

The PLANTS2 data file gives data on four different species of plants grown in a laboratory. The species are Leucaena leucocephala, Acacia saligna, Prosopis juliflora, and Eucalyptus citriodora. The researchers who collected these data were interested in commercially growing these plants in parts of the country of Jordan where there is very little rainfall. To examine the effect of water, they varied the amount per day from 50 millimeters (mm) to 650 mm in 100 mm increments. There were four plants per species-by-water combination. There are two response variables. They are fresh biomass and dry biomass. High values for both of these variables are desirable.

Examine the residuals for the two response variables. Are there any unusual patterns or outliers? If you think that there are one or more points that are somewhat extreme, rerun the two-way analysis without these observations. Does this change the results in any substantial way?

TABLE 13.2 Tool diameter data Tool Time Diameter 25.030 25.030 25.032 25.028 25.028 25.028 25.026 25.026 25.026 25.016 25.018 25.016 25.022 25.020 25.018 25.016 25.016 25.016 1 25.005 25.008 25.006 25.012 25.012 25.014 25.010 25.010 25.008 25.012 25.012 25.012 25.018 25.020 25.020 25.010 25.014 25.018 24.996 24.998 24.998 25.006 25.006 25.006 25.000 25.002 24.999 Table 13-2 to the Practice of Statistics, Fifth Edition o 200SW,H Freeman and Company

Explanation / Answer

Result:

Examine the residuals for the two response variables. Are there any unusual patterns or outliers? If you think that there are one or more points that are somewhat extreme, rerun the two-way analysis without these observations. Does this change the results in any substantial way?

MINITAB used

General Linear Model: fbiomass versus species, water

Method

Factor coding (-1, 0, +1)

Factor Information

Factor   Type   Levels Values

species Fixed       4 1, 2, 3, 4

water    Fixed       7 1, 2, 3, 4, 5, 6, 7

Analysis of Variance

Source            DF   Adj SS Adj MS F-Value P-Value

species          3   458295 152765    81.45    0.000

water            6   491948   81991    43.71    0.000

species*water   18    60334    3352     1.79    0.040

Error             84   157551    1876

Total            111 1168129

Model Summary

      S    R-sq R-sq(adj) R-sq(pred)

43.3083 86.51%     82.18%      76.02%

Fits and Diagnostics for Unusual Observations

Obs fbiomass    Fit   Resid Std Resid

44     184.8 266.0   -81.2      -2.17 R

50     422.9 343.3    79.7       2.12 R

52     199.5 343.3 -143.8      -3.83 R

53     555.3 397.4   157.9       4.21 R

55     311.1 397.4   -86.3      -2.30 R

R Large residual

The main effects species and water, interaction effects all are significant.

Observations 52 and 53 are large residuals.

After removing 52 and 53,

General Linear Model: fbiomass versus species, water

Method

Factor coding (-1, 0, +1)

Factor Information

Factor   Type   Levels Values

species Fixed       4 1, 2, 3, 4

water    Fixed       7 1, 2, 3, 4, 5, 6, 7

Analysis of Variance

Source            DF   Adj SS Adj MS F-Value P-Value

species          3   437130 145710   123.54    0.000

water            6   478487   79748    67.61    0.000

species*water   18    51868    2882     2.44    0.003

Error             82    96717   1179

Total            109 1028234

Model Summary

      S    R-sq R-sq(adj) R-sq(pred)

34.3435 90.59%     87.50%      83.13%

After removing the extreme values results are not changed.

General Linear Model: dbiomass versus species, water

Method

Factor coding (-1, 0, +1)

Factor Information

Factor   Type   Levels Values

species Fixed       4 1, 2, 3, 4

water    Fixed       7 1, 2, 3, 4, 5, 6, 7

Analysis of Variance

Source            DF Adj SS   Adj MS F-Value P-Value

species          3   50524 16841.3    79.93    0.000

water            6   56624   9437.3    44.79    0.000

species*water   18    8419    467.7     2.22    0.008

Error             84   17698    210.7

Total            111 133265

Model Summary

      S    R-sq R-sq(adj) R-sq(pred)

14.5153 86.72%     82.45%      76.39%

Coefficients

Fits and Diagnostics for Unusual Observations

Obs dbiomass     Fit   Resid Std Resid

44     59.14   95.10 -35.96      -2.86 R

48     79.80 106.81 -27.01      -2.15 R

52     65.17 103.18 -38.01      -3.02 R

53    172.65 119.62   53.03       4.22 R

111     78.85   53.60   25.25       2.01 R

R Large residual

The main effects species and water, interaction effects all are significant.

Observations 52 and 53 are large residuals.

After removing 52 and 53,

General Linear Model: dbiomass versus species, water

Method

Factor coding (-1, 0, +1)

Factor Information

Factor   Type   Levels Values

species Fixed       4 1, 2, 3, 4

water    Fixed       7 1, 2, 3, 4, 5, 6, 7

Analysis of Variance

Source            DF Adj SS   Adj MS F-Value P-Value

species          3   48947 16315.5   111.27    0.000

water            6   54798   9133.1    62.29    0.000

species*water   18    7383    410.1     2.80    0.001

Error             82   12023    146.6

Total            109 121859

Model Summary

      S    R-sq R-sq(adj) R-sq(pred)

12.1088 90.13%     86.88%     82.41%

After removing the extreme values results are not changed.

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