Answer:1.27,2.83,3.73.
Step-by-step explanation: 1.27 becuase when you add and subtract
Answer:
80 / 60 = 1.3 approximately
Step-by-step explanation:
The pattern for this is least to greatest
Answer:
Well, these simulation are based on the statistics (lognormal-distributed PE, χ²-distributed s²). If you believe that only the ‘gold-standard’ of subject-simulations are valid, we can misuse the function sampleN.scABEL.sdsims() – only for the 3- and 4-period full replicates and the partial replicate:
# define a reg_const where all scaling conditions are ‘switched off’
abe <- reg_const("USER", r_const = NA, CVswitch = Inf,
CVcap = Inf, pe_constr = FALSE)
CV <- 0.4
2x2x4 0.05 0.4 0.4 0.95 0.8 1.25 34 0.819161 0.8
Since the sample sizes obtained by all simulations match the exact method, we can be confident that it is correct. As usual with a higher number of simulations power gets closer to the exact value.
Step-by-step explanation:
Answer:
last week = 150 minutes
this week = 162 minutes
changes = 162-150
= 12 minutes
percentage of changes = (12/150) × 100
= 8%
