A Kansas University research station wishes to investigate if a new variety of wheat is more resistant to a disease than an old variety. It is known that this disease strikes approximately 15% of all plants of the old variety. A field experiment was conducted, and of 120 new plants, 12 became infected.
The calculated value of the test statistic is:
1.83
1.10
-1.53
1.53
1.83
To determine the calculated value of the test statistic in this scenario, we need to perform a hypothesis test. The test statistic used depends on the type of hypothesis test being conducted. In this case, we are comparing two proportions, so we will use the Z-test statistic.
The Z-test statistic can be calculated using the following formula:
Z = (p1 - p2) / sqrt( (p1(1-p1)/n1) + (p2(1-p2)/n2) )
Where:
p1 is the proportion of plants infected in the old variety
p2 is the proportion of plants infected in the new variety
n1 is the sample size of the old variety
n2 is the sample size of the new variety
From the given information, we can calculate the values:
p1 = 0.15 (15%)
p2 = 12/120 = 0.10 (10%)
n1 is not given
n2 = 120
Without the sample size of the old variety (n1), we cannot calculate the exact test statistic value. Therefore, we do not have enough information to determine the calculated value of the test statistic from the options provided.