Answer:
the new Zealand international was the first time he had scored in a day and a half century for any of his
Answer:
The variance in weight is statistically the same among Javier's and Linda's rats
The null hypothesis will be accepted because the P-value (0.53 ) > ∝ ( level of significance )
Step-by-step explanation:
considering the null hypothesis that there is no difference between the weights of the rats, we will test the weight gain of the rats at 10% significance level with the use of Ti-83 calculator
The results from the One- way ANOVA ( Numerator )
with the use of Ti-83 calculator
F = .66853
p = .53054
Factor
df = 2 ( degree of freedom )
SS = 23.212
MS = 11.606
Results from One-way Anova ( denominator )
Ms = 11.606
Error
df = 12 ( degree of freedom )
SS = 208.324
MS = 17.3603
Sxp = 4.16657
where : test statistic = 0.6685
p-value = 0.53
level of significance ( ∝ ) = 0.10
The null hypothesis will be accepted because the P-value (0.53 ) > ∝
where Null hypothesis H0 = ∪1 = ∪2 = ∪3
hence The variance in weight is statistically the same among Javier's and Linda's rats
Benchmark are numbers that are used as standards to which the rest of the data is compared to. When counting numbers using a number line, the benchmark numbers are the intervals written on the axis. For benchmark numbers of 10, the number line on top of the attached picture is shown. Starting from 170, the tick marks are added by 10, such that the next numbers are 180, 190, 200, and so on and so forth. When you want to find 410, just find the benchmark number 410.
The same applies to benchmark numbers in intervals of 100. If you want to find 170, used the benchmark numbers 100 and 200. Then, you estimate at which point represents 170. For 410, you base on the benchmark numbers 400 and 500.