5.4. To establish whether RATE is indeed needed to predict the effectiveness of a treatment, a formal test can be used. Give the name of this test, state the hypothesis, test statistic formula and the decision rule.

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5.1. A study was conducted to ascertain the effectiveness of a treatment of diseased plants. A recorded
value of Y = 1 indicates that the treatment is effective and a value of Y = 0 is recorded when no
effect is noticed. The outcome of the effectiveness of the treatment considers the treatment
dosage, the above ground biomass, the rate of growth and the height of a plant recorded as 1 if
above average height and recorded 0 as below average height. The following partial data set is
provided.
EFFECTS (Y) DOSAGE X₁
0.2138
0.3907
0.2138
1
1
0
The output for running the full logistic regression model is given below:
Coefficients
(Intercept)
HEIGHT
BIOMASS
RATE
DOSAGE
Coefficients
RATE
(Intercept)
BIOMASS
Estimate
-1.23
0.31
0.33
0.34
-1.86
Log Likelihood: - 2.579
The output for the reduced model is given below:
Estimate
-1.25
0.21
BIOMASS X₂ RATE X3
0.0525
1.1
0.0264
1.2
0.0920
1.3
0.41
Log Likelihood: -4.246
Answer the following questions.
Std. Error
0.6795
0.6821
5.9374
2.4112
2.1420
Std. Error
0.4129
4.7390
2.4223
6
z value
-1.653
0.456
2.594
3.167
-0866
z value
-2.488
2.572
3.161
HEIGHT X4
0
1
1
Pr(>Z)
0.0984
0.6484
0.0095
0.0076
0.3864
Pr(>Z)
0.0144
0.0101
0.0076
5.4. To establish whether RATE is indeed needed to predict the effectiveness of a treatment, a formal
test can be used. Give the name of this test, state the hypothesis, test statistic formula and the
decision rule.
Transcribed Image Text:5.1. A study was conducted to ascertain the effectiveness of a treatment of diseased plants. A recorded value of Y = 1 indicates that the treatment is effective and a value of Y = 0 is recorded when no effect is noticed. The outcome of the effectiveness of the treatment considers the treatment dosage, the above ground biomass, the rate of growth and the height of a plant recorded as 1 if above average height and recorded 0 as below average height. The following partial data set is provided. EFFECTS (Y) DOSAGE X₁ 0.2138 0.3907 0.2138 1 1 0 The output for running the full logistic regression model is given below: Coefficients (Intercept) HEIGHT BIOMASS RATE DOSAGE Coefficients RATE (Intercept) BIOMASS Estimate -1.23 0.31 0.33 0.34 -1.86 Log Likelihood: - 2.579 The output for the reduced model is given below: Estimate -1.25 0.21 BIOMASS X₂ RATE X3 0.0525 1.1 0.0264 1.2 0.0920 1.3 0.41 Log Likelihood: -4.246 Answer the following questions. Std. Error 0.6795 0.6821 5.9374 2.4112 2.1420 Std. Error 0.4129 4.7390 2.4223 6 z value -1.653 0.456 2.594 3.167 -0866 z value -2.488 2.572 3.161 HEIGHT X4 0 1 1 Pr(>Z) 0.0984 0.6484 0.0095 0.0076 0.3864 Pr(>Z) 0.0144 0.0101 0.0076 5.4. To establish whether RATE is indeed needed to predict the effectiveness of a treatment, a formal test can be used. Give the name of this test, state the hypothesis, test statistic formula and the decision rule.
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